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Journal articles on the topic 'Emojis'
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1
Dirgayasa, I. Wayan. "EMOJI, A BREAKTHROUGH IN CONTEMPORARY COMMUNICATION (A LITERATURE REVIEW)." Journal of Language, Literature, and Teaching 4, no. 2 (November 20, 2022): 63–76. http://dx.doi.org/10.35529/jllte.v4i2.63-76.
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It is a fact that emojis are a growing phenomenon in the last few years. They have gained their popularity with their typical varieties in the digital era across countries in the world. The emojis are used among people as a way to assist the process of conveying emotions in textual communication that lacks nonlinguistic cues. Emojis were created and developed as visual mixed expressions of sentiments, attitudes, or moods for use in modern communication technologies. Then, in more broad perspective and context, in term usages, they are also generally perceived that they do not only have unique semantic and emotional features, but also are closely related to many areas such as marketing, law, education, health, etc. This paper reviews the nature of emoji, the developmental history of emojis, the functions of emojis in communication, and the usages of emojis in a real-digital world interaction and communication. Key words: emoji, function of emojis in communication, and the usages of emoji in digital world.
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Weissman, Benjamin. "Peaches and eggplants or. . . something else? The role of context in emoji interpretations." Proceedings of the Linguistic Society of America 4, no. 1 (March 15, 2019): 29. http://dx.doi.org/10.3765/plsa.v4i1.4533.
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This paper presents the results of an experiment designed to measure interpretations of two emojis oft-discussed in popular culture, the eggplant and the peach. The experiment asked people to judge how sexual an emoji-containing text message was. The context surrounding these messages was manipulated across experimental conditions, altering both the preceding discourse and the presence of a sentence-final wink emoji. Unsurprisingly, the baseline interpretation of both the eggplant and peach emoji is euphemism. When one of these emojis is used in a context that strongly biases towards the non-euphemistic interpretation, ratings for sexualness decrease and variability increases. This suggests that participants are still able to access non-euphemistic interpretations of these emojis, but it must be under specific circumstances and will nonetheless come with a high degree of variability. Wink emojis added to messages containing non-euphemistic food emojis were also rated as more highly sexual (albeit still low on the rating scale), indicating an affective role for this emoji.
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Hu, Tianran, Han Guo, Hao Sun, Thuy-vy Nguyen, and Jiebo Luo. "Spice Up Your Chat: The Intentions and Sentiment Effects of Using Emojis." Proceedings of the International AAAI Conference on Web and Social Media 11, no. 1 (May 3, 2017): 102–11. http://dx.doi.org/10.1609/icwsm.v11i1.14869.
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Emojis, as a new way of conveying nonverbal cues, are widely adopted in computer-mediated communications. In this paper, first from a message sender perspective, we focus on people's motives in using four types of emojis — positive, neutral, negative, and non-facial. We compare the willingness levels of using these emoji types for seven typical intentions that people usually apply nonverbal cues for in communication. The results of extensive statistical hypothesis tests not only report the popularities of the intentions, but also uncover the subtle differences between emoji types in terms of intended uses. Second, from a perspective of message recipients, we further study the sentiment effects of emojis, as well as their duplications, on verbal messages. Different from previous studies in emoji sentiment, we study the sentiments of emojis and their contexts as a whole. The experiment results indicate that the powers of conveying sentiment are different between four emoji types, and the sentiment effects of emojis vary in the contexts of different valences.
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Murthy, Dhiraj, Sabitha Sudarshan, Jung-Ah Lee, Charulata Ghosh, Pratik Shah, Wei-Jie Xiao, Ishank Arora, Clive Unger, and Amelia Acker. "Understanding the meaning of emoji in mobile social payments: Exploring the use of mobile payments as hedonic versus utilitarian through skin tone modified emoji usage." Big Data & Society 7, no. 2 (July 2020): 205395172094956. http://dx.doi.org/10.1177/2053951720949564.
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Despite research establishing emojis as sites of critical racial discourse, there is a paucity of literature examining their importance in the increasingly popular context of mobile payments. This is particularly important as new forms of social payment platforms such as Venmo bridge the seamlessness of mobile payments with the vibrant communicative practices of social networks. As such, they provide a unique medium to examine how emojis are used within the context of digital consumption, and by extension, self-representation. This study analyzes approximately 325 million public transactions on the U.S. payment platform Venmo to understand whether emoji usage in mobile payments is more hedonic or utilitarian. We then explore how race is represented across emoji usage on Venmo via tone-modified emojis, a subset of emojis whereby users can choose a skin tone. We found that while emojis in general are used for more hedonic purposes than utilitarian ones, darker tone-modified emojis indicate a proportionately higher use in hedonic consumption as compared to lighter tone-modified emojis, and also show a higher representation of utilitarian categories in transactions. Thematic analysis revealed that subsets with darker tone-modified emojis have a greater lexical variety and engage in more playful uses of emoji in mobile payments
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Tomihira, Toshiki, Atsushi Otsuka, Akihiro Yamashita, and Tetsuji Satoh. "Multilingual emoji prediction using BERT for sentiment analysis." International Journal of Web Information Systems 16, no. 3 (September 21, 2020): 265–80. http://dx.doi.org/10.1108/ijwis-09-2019-0042.
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Purpose Recently, Unicode has been standardized with the penetration of social networking services, the use of emojis has become common. Emojis, as they are also known, are most effective in expressing emotions in sentences. Sentiment analysis in natural language processing manually labels emotions for sentences. The authors can predict sentiment using emoji of text posted on social media without labeling manually. The purpose of this paper is to propose a new model that learns from sentences using emojis as labels, collecting English and Japanese tweets from Twitter as the corpus. The authors verify and compare multiple models based on attention long short-term memory (LSTM) and convolutional neural networks (CNN) and Bidirectional Encoder Representations from Transformers (BERT). Design/methodology/approach The authors collected 2,661 kinds of emoji registered as Unicode characters from tweets using Twitter application programming interface. It is a total of 6,149,410 tweets in Japanese. First, the authors visualized a vector space produced by the emojis by Word2Vec. In addition, the authors found that emojis and similar meaning words of emojis are adjacent and verify that emoji can be used for sentiment analysis. Second, it involves entering a line of tweets containing emojis, learning and testing with that emoji as a label. The authors compared the BERT model with the conventional models [CNN, FastText and Attention bidirectional long short-term memory (BiLSTM)] that were high scores in the previous study. Findings Visualized the vector space of Word2Vec, the authors found that emojis and similar meaning words of emojis are adjacent and verify that emoji can be used for sentiment analysis. The authors obtained a higher score with BERT models compared to the conventional model. Therefore, the sophisticated experiments demonstrate that they improved the score over the conventional model in two languages. General emoji prediction is greatly influenced by context. In addition, the score may be lowered due to a misunderstanding of meaning. By using BERT based on a bi-directional transformer, the authors can consider the context. Practical implications The authors can find emoji in the output words by typing a word using an input method editor (IME). The current IME only considers the most latest inputted word, although it is possible to recommend emojis considering the context of the inputted sentence in this study. Therefore, the research can be used to improve IME performance in the future. Originality/value In the paper, the authors focus on multilingual emoji prediction. This is the first attempt of comparison at emoji prediction between Japanese and English. In addition, it is also the first attempt to use the BERT model based on the transformer for predicting limited emojis although the transformer is known to be effective for various NLP tasks. The authors found that a bidirectional transformer is suitable for emoji prediction.
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Santos, Luana, Natália Alencar, Jéssica Rodrigues, Aline Gonçalves, and Felipe Trombete. "Proposal of two facial scales using emojis as tools to understand emotions in research with Brazilian consumers." Acta Scientiarum. Technology 44 (January 12, 2022): e56610. http://dx.doi.org/10.4025/actascitechnol.v44i1.56610.
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Emojis are used in digital communication to express feelings and emotions and are commonly used on social media platforms. Research aiming to interpret the meaning of facial emojis is needed and should consider differences among several characteristics as the cultural aspects across different countries. This study aimed to assess the meaning of emojis by Brazilians and create two facial scales that can be used in later research with applications of emojis in consumer studies and sensory analysis of food and beverages. The associations between emotions and emojis were evaluated by 132 participants from Brazil using 39 descriptive terms and 33 facial emojis through a modified Check-All-That-Apply (CATA) questionnaire. The overall average of emoji associations for each CATA term varied from 1.1 to 4.3, demonstrating that the associations varied a lot, depending on the emotion. In this way, it was possible to obtain a group of emotions with a strong association with one emoji (n=15); a second group with a strong association with more than one emoji (n=8), and; a third group with weak associations (n=16). The emojis from the first and second groups were used to make a chart with 14 emojis to be used in consumer research with Brazilian consumers and also a 5-point facial scale of intensity to be used in sensory analysis with food and beverages.
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Sabri, Ahmad Fakrusy Syakirin Ahmad, Siti Zanariah Yusoff, and Isyaku Hassan. "Exploring emoji as a viable cultural tool in WhatsApp communications among Malaysian undergraduates." LAPLAGE EM REVISTA 7, no. 3D (October 13, 2021): 351–62. http://dx.doi.org/10.24115/s2446-6220202173d1727p.351-362.
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An emoji is a form of a symbol in communication available on almost all social media platforms. Its convenience brings potential implications for its usage in digital communication. This study aims to explore the effectiveness of emojis in WhatsApp communication and the influence of culture on emoji usage among undergraduates in Malaysia. The study employed a qualitative approach in which semi-structured interviews were conducted with eight undergraduates of Universiti Sultan Zainal Abidin (UniSZA). The data were analyzed using inductive thematic analysis. Overall, the findings revealed that emojis increase communication efficiency. The participants have positive attitudes towards emoji usage. They describe emojis as viable symbols that help them to maintain social relations and express feelings. Additionally, the findings showed that Malaysian culture influences emoji communication by promoting harmony and relationships as well as instilling high context values in emoji usage. This research concludes that emojis can influence WhatsApp Communication positively if utilized correctly.
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Gao, Biao, Xingxing Wang, and Han Liu. "An Empirical Study on the Communication and Usage Psychology of Emoji in Wechat." OBM Neurobiology 06, no. 04 (October 17, 2022): 1–18. http://dx.doi.org/10.21926/obm.neurobiol.2204142.
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As an indispensable active atmosphere and meaningful emotional expression in social media, emojis describe the emotions of users in specific situations in a funny, humorous, euphemistic, and implicit form and attract users to use them consciously or unconsciously with their quick and convenient features. Currently, the research on the psychology of emoji usage is mostly from the perspective of users, while neglecting the essential attributes of emojis. The purpose of this study was to investigate and summarize the multi-dimensional factors that affect the communication and usage of emojis and to elucidate the influence of the essential attributes of emojis on their use. This study took the users of WeChat (the most widely used instant messaging app in China) as the research object. Data were collected utilizing semi-structured interviews and questionnaires. SPSS 25.0 software was applied to conduct exploratory factor analysis on relevant data to explore and summarize several dimensions of WeChat users’ emoji communication and usage psychology. The results showed that gender, age, education, and occupation were important factors affecting the usage and communication of emojis. The psychology of emoji usage had multi-dimensional characteristics and according to the self-determination theory, it could be divided into internal and external factors. The internal factors included information, efficiency, and entertainment, and the external factors included communicativeness, culture, image, fuzziness, and context. Notably, the influence of fuzziness on the psychology of emoji usage has described the critical role of the essential attributes of emojis, which complemented the neglect of the fuzziness of emoji in previous studies, which might provide a direction for the design of emojis.
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Mudure-Iacob, Ioana. "Mapping Language Learning With Emojis: From Phatic Communication to Idioms and Flash Fiction." Studia Universitatis Babeș-Bolyai Philologia 67, no. 4 (December 20, 2022): 275–94. http://dx.doi.org/10.24193/subbphilo.2022.4.14.
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"Mapping Language Learning with Emojis: From Phatic Communication to Idioms and Flash Fiction. By roaming around digital resources in search of a customised learning approach, language learners often identify as netizens accustomed to a coded Internet language which is rarely juxtaposed with the language taught in the ESP classroom. To keep pace with shifting trends in online communication, teachers often need to expand the discursive membership by empowering learners to turn from users into content creators. By referring to the potential of using emojis in the framework of speech acts, the current paper aims to indicate directions of embedding emojis as social marking tokens and instruments of developing language and digital literacy skills in the foreign language class. The process of embedding emojis in language teaching stems from the integration of emoji as markers in the teaching of phatic communication, to reinforce the locutionary and illocutionary act of speech. Moreover, emojis can be used as an extension of teaching idioms, whereas the illocutionary and perlocutionary function of emoji is explored in interactive vocabulary practice tasks or within gamified sequences. Eventually, using emojis as perlocutionary acts in language learning is applied to storytelling as a mechanism of developing a multiliterate discourse, by means of which learners are introduced to writing emoji stories and flash fictions and then to translating them into words. Keywords: emojis, content creators, speech acts, multimodality, participatory culture "
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Częstochowska, Justyna, Kristina Gligorić, Maxime Peyrard, Yann Mentha, Michał Bień, Andrea Grütter, Anita Auer, Aris Xanthos, and Robert West. "On the Context-Free Ambiguity of Emoji." Proceedings of the International AAAI Conference on Web and Social Media 16 (May 31, 2022): 1388–92. http://dx.doi.org/10.1609/icwsm.v16i1.19393.
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Due to their pictographic nature, emojis come with baked-in, grounded semantics. Although this makes emojis promising candidates for new forms of more accessible communication, it is still unknown to what degree humans agree on the inherent meaning of emojis when encountering them outside of concrete textual contexts. To bridge this gap, we collected a crowdsourced dataset (made publicly available) of one-word descriptions for 1,289 emojis presented to participants with no surrounding text. The emojis and their interpretations were then examined for ambiguity. We find that, with 30 annotations per emoji, 16 emojis (1.2%) are completely unambiguous, whereas 55 emojis (4.3%) are so ambiguous that the variation in their descriptions is as high as that in randomly chosen descriptions. Most emojis lie between these two extremes. Furthermore, investigating the ambiguity of different types of emojis, we find that emojis representing symbols from established, yet not cross-culturally familiar code books (e.g., zodiac signs, Chinese characters) are most ambiguous. We conclude by discussing design implications.
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Li, Mengdi, Eugene Chng, Alain Yee Loong Chong, and Simon See. "An empirical analysis of emoji usage on Twitter." Industrial Management & Data Systems 119, no. 8 (September 9, 2019): 1748–63. http://dx.doi.org/10.1108/imds-01-2019-0001.
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Purpose Emoji has become an essential component of any digital communication and its importance can be attested to by its sustained popularity and widespread use. However, research in Emojis is rarely to be seen due to the lack of data at a greater scale. The purpose of this paper is to systematically analyse and compare the usage of Emojis in a cross-cultural manner. Design/methodology/approach This research conducted an empirical analysis using a large-scale, cross-regional emoji usage data set from Twitter, a platform where the limited 140 characters allowance has made it essential for the inclusion of emojis within tweets. The extremely large textual data set covers a period of only two months, but the 673m tweets authored by more than 2,081,542 unique users is a sufficiently large sample for the authors to yield significant results. Findings This research discovered that the categories and frequencies of Emojis communicated by users can provide a rich source of data to understand cultural differences between Twitter users from a large range of demographics. This research subsequently demonstrated the preferential use of Emojis complies with Hofstede’s Cultural Dimensions Model, in which different representations of demographics and culture within countries present significantly different use of Emojis to communicate emotions. Originality/value This study provides a robust example of how to strategically conduct research using large-scale emoji data to pursue research questions previously difficult. To the best of authors’ knowledge, the present study pioneers the first systematic analysis and comparison of the usage of emojis on Twitter across different cultures; it is the largest, in terms of the scale study of emoji usage to-date.
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Bajcsi, Anna, Barbara Botos, Péter Bajkó, and Zalán Bodó. "Can You Guess the Title? Generating Emoji Sequences for Movies." Studia Universitatis Babeș-Bolyai Informatica 67, no. 1 (July 3, 2022): 5–20. http://dx.doi.org/10.24193/subbi.2022.1.01.
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"In the culture of the present emojis play an important role in written/typed communication, having a primary role of supplementing the words with emotional cues. While in different cultures emojis can be interpreted and thus used differently, a small set of emojis have clear meaning and strong sentiment polarity. In this work we study how to map natural language texts to emoji sequences, more precisely, we automatically assign emojis to movie subtitles/scripts. The pipeline of the proposed method is as follows: first the most relevant words are extracted from the movie subtitle, and then these are mapped to emojis. In order to perform the mapping, three methods are proposed: a lexical matching-based, a word embedding-based and a combined approach. To demonstrate the viability of the approach, we list some of the generated emojis for a randomly selected movie subset, showing also the deficiencies of the method in generating guessable sequences. Evaluation is performed via quizzes completed by human participants. Keywords and phrases: natural language processing, emoji, keyword extraction, movie scripts, lexical matching, word embedding. "
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Anu Kiruthika M. and Angelin Gladston. "Implementation of Recurrent Network for Emotion Recognition of Twitter Data." International Journal of Social Media and Online Communities 12, no. 1 (January 2020): 1–13. http://dx.doi.org/10.4018/ijsmoc.2020010101.
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A new generation of emoticons, called emojis, is being largely used for both mobile and social media communications. Emojis are considered a graphic expression of emotions, and users have been widely used to express their emotions in social media. Emojis are graphic unicode symbols used to express perceptions, views, and ideas as a shorthand. Unlike the small number of well-known emoticons carrying clear emotional content, hundreds of emojis are being used in different social networks. The task of emoji emotion recognition is to predict the original emoji in a tweet. Recurrent neural network is used for building emoji emotion recognition system. Glove is a word-embedding method used for obtaining vector representation of words and are used for training the recurrent neural network. This is achieved by mapping words into a meaningful space where the distance between words is related to semantic similarity. Based on the word embedding in the Twitter dataset, recurrent neural network builds the model and finally predicts the emoji associated with the tweets with an accuracy of 83%.
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Al-Zou’bi, Reem, and Fathi Shamma. "Assessing instructors’ usage of emojis in distance education during the COVID-19 pandemic." Cypriot Journal of Educational Sciences 16, no. 1 (February 25, 2021): 201–20. http://dx.doi.org/10.18844/cjes.v16i1.5520.
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This research assessed instructors’ usage of emojis in distance education for high diploma students. A quantitative approach was employed comprising an e-survey consisting of 11-items, one closed-ended question, and two open-ended questions. The participants were a randomly selected sample of 343 high diploma students, 243 attending Al al-Bayt University (AABU) in Jordan and 100 students attending the Arab Academic College in Haifa (AAC). The results indicated that instructors’ usage of emojis in distance education was moderate in both universities. All students strongly preferred instructors to use emojis to express what is on their minds as an alternative to facial expressions, and female instructors were more active in using emojis in virtual lectures. The emoji used most frequently by distance education instructors for the sample was the thumbs-up emoji ( ). Based on the results, several recommendations are put forth that will be of value to researchers and workers in this field.
Keywords: Distance Education; Emojis; COVID-19
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Ai, Wei, Xuan Lu, Xuanzhe Liu, Ning Wang, Gang Huang, and Qiaozhu Mei. "Untangling Emoji Popularity Through Semantic Embeddings." Proceedings of the International AAAI Conference on Web and Social Media 11, no. 1 (April 30, 2017): 2–11. http://dx.doi.org/10.1609/icwsm.v11i1.14903.
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Emojis have gone viral on the Internet across platforms and devices. Interwoven into our daily communications, they have become a ubiquitous new language. However, little has been done to analyze the usage of emojis at scale and in depth. Why do some emojis become especially popular while others don't? How are people using them among the words? In this work, we take the initiative to study the collective usage and behavior of emojis, and specifically, how emojis interact with their context. We base our analysis on a very large corpus collected from a popular emoji keyboard, which contains a full month of inputs from millions of users. Our analysis is empowered by a state-of-the-art machine learning tool that computes the embeddings of emojis and words in a semantic space. We find that emojis with clear semantic meanings are more likely to be adopted. While entity-related emojis are more likely to be used as alternatives to words, sentiment-related emojis often play a complementary role in a message. Overall, emojis are significantly more prevalent in a sentimental context.
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Chandra Guntuku, Sharath, Mingyang Li, Louis Tay, and Lyle H. Ungar. "Studying Cultural Differences in Emoji Usage across the East and the West." Proceedings of the International AAAI Conference on Web and Social Media 13 (July 6, 2019): 226–35. http://dx.doi.org/10.1609/icwsm.v13i01.3224.
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Global acceptance of Emojis suggests a cross-cultural, normative use of Emojis. Meanwhile, nuances in Emoji use across cultures may also exist due to linguistic differences in expressing emotions and diversity in conceptualizing topics. Indeed, literature in cross-cultural psychology has found both normative and culture-specific ways in which emotions are expressed. In this paper, using social media, we compare the Emoji usage based on frequency, context, and topic associations across countries in the East (China and Japan) and the West (United States, United Kingdom, and Canada). Across the East and the West, our study examines a) similarities and differences on the usage of different categories of Emojis such as People, Food & Drink, Travel & Places etc., b) potential mapping of Emoji use differences with previously identified cultural differences in users’ expression about diverse concepts such as death, money emotions and family, and c) relative correspondence of validated psycho-linguistic categories with Ekman’s emotions. The analysis of Emoji use in the East and the West reveals recognizable normative and culture specific patterns. This research reveals the ways in which Emojis can be used for cross-cultural communication.
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Hardiyanti, Waode Eti, Muhammad Ilham, Aris Suziman, and Astriyani Astriyani. "PENGGUNAAN EMOJI UNTUK MENINGKATKAN PERILAKU BAIK (WELL-BEING) DAN KEMAMPUAN BAHASA ANAK USIA DINI." EARLY CHILDHOOD : JURNAL PENDIDIKAN 3, no. 2 (July 14, 2020): 15–25. http://dx.doi.org/10.35568/earlychildhood.v3i2.653.
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This study aims to improve children’s well-being and communication skills using emoji as a learning media. Emoji images used consist of facial emojis, objects and activities that are easily understood and close to children’s daily experiences. The techniques of collecting data were observation sheet and direct observation by researchers. This study used a qualitative descriptive method and the samples were 25 children, collected through purposive sampling, aged between 5-6 years in one PAUD in Konawe Selatan. The results of this study found that emoji media can positively improve children’s well-being and their language abilities. Children always showed huge interest when imitating, affirming, explaining and connecting emojis with objects and their feelings. Children told their daily experiences associated with emojis, hence they become the center of learning where their opinion and ideas are truly heard and understood, which is an important indicator to improve children’s well-being. The open-ended nature of emojis makes children have the opportunity to discuss emoji symbols that are correct according to them and also help researchers interpret how children see their own world. Meanwhile, language ability aspects increased during this activity were vocabulary, the children ability to provide definition, solutions and examples of certain problems, and self-confidence.
Keywords: children well-being; emoji; communication skill; preschools
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Haltmayer, Vanessa, and Heribert Gierl. "Emoji Your Story: The Advertising Effectiveness of Emoji-Based Narratives." Marketing ZFP 43, no. 1-2 (2021): 67–94. http://dx.doi.org/10.15358/0344-1369-2021-1-2-67.
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Emojis are often used as single symbols to express emotions. Moreover, they serve as paralanguage in mass media and digital communication. Emojis are also used to tell narratives in advertising. Thus far, the latter usage of emojis has not been investigated. In two studies, we investigated the effectiveness of emoji-based narratives compared with textual narratives. Based on the data obtained from a thought-listing task, we found that consumers focus on solving the emoji puzzle when emojis are presented, whereas textual narratives are seldom replicated in such detail and induce additional thoughts about product features. We found the following five mediating effects: emoji-based narratives influence brand attitudes and the propensity to follow recommendations (provided in social-marketing campaigns) through 1. higher levels of narrative transportation, 2. higher perceptions of ad originality, 3. lower message comprehensibility, 4. stronger curiosity, and 5. lower perceptions of brand/organization trustworthiness. In total, emoji puzzles proved to be advantageous compared with textual narratives, with one exception: if the ad promoted advice that had no immediate and direct relevance for to the consumers’ lives (e.g., avoiding the use of animal-tested cosmetics and contributing to the preservation of the Amazon rainforest), the participants showed a low propensity to solve the emoji puzzle.
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Liebeskind, Chaya. "Emoji Identification and Prediction in Hebrew Political Corpus." Issues in Informing Science and Information Technology 16 (2019): 343–59. http://dx.doi.org/10.28945/4372.
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Aim/Purpose: Any system that aims to address the task of modeling social media communication need to deal with the usage of emojis. Efficient prediction of the most likely emoji given the text of a message may help to improve different NLP tasks. Background: We explore two tasks: emoji identification and emoji prediction. While emoji prediction is a classification task of predicting the emojis that appear in a given text message, emoji identification is the complementary preceding task of determining if a given text message includes emojies. Methodology: We adopt a supervised Machine Learning (ML) approach. We compare two text representation approaches, i.e., n-grams and character n-grams and analyze the contribution of additional metadata features to the classification. Contribution: The task of emoji identification is novel. We extend the definition of the emoji prediction task by allowing to use not only the textual content but also meta-data analysis. Findings: Metadata improve the classification accuracy in the task of emoji identification. In the task of emoji prediction it is better to apply feature selection. Recommendations for Practitioners: In many of the cases the classifier decision seems fitter to the comment content than the emoji that was chosen by the commentator. The classifier may be useful for emoji suggestion. Recommendation for Researchers: Explore character-based representations rather than word-based representations in the case of morphologically rich languages. Impact on Society: Improve the modeling of social media communication. Future Research: We plan to address the multi-label setting of the emoji prediction task and to investigate the deep learning approach for both of our classification tasks
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Lu, Xuan, Wei Ai, Zhenpeng Chen, Yanbin Cao, and Qiaozhu Mei. "Emojis predict dropouts of remote workers: An empirical study of emoji usage on GitHub." PLOS ONE 17, no. 1 (January 26, 2022): e0261262. http://dx.doi.org/10.1371/journal.pone.0261262.
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Emotions at work have long been identified as critical signals of work motivations, status, and attitudes, and as predictors of various work-related outcomes. When more and more employees work remotely, these emotional signals of workers become harder to observe through daily, face-to-face communications. The use of online platforms to communicate and collaborate at work provides an alternative channel to monitor the emotions of workers. This paper studies how emojis, as non-verbal cues in online communications, can be used for such purposes and how the emotional signals in emoji usage can be used to predict future behavior of workers. In particular, we present how the developers on GitHub use emojis in their work-related activities. We show that developers have diverse patterns of emoji usage, which can be related to their working status including activity levels, types of work, types of communications, time management, and other behavioral patterns. Developers who use emojis in their posts are significantly less likely to dropout from the online work platform. Surprisingly, solely using emoji usage as features, standard machine learning models can predict future dropouts of developers at a satisfactory accuracy. Features related to the general use and the emotions of emojis appear to be important factors, while they do not rule out paths through other purposes of emoji use.
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Danesi, Marcel. "Emojis: Langue or Parole?" Chinese Semiotic Studies 15, no. 2 (May 30, 2019): 243–58. http://dx.doi.org/10.1515/css-2019-0015.
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Abstract The phenomenon of emojis has had many implications for the future course of writing, literacy, communications, and the nature of representation itself. This paper looks at the implications of emoji use through the filter of Saussurean semiotics and through the lens of theories of visuality, which claim that visual writing is having radical effects on literacy and cognition. The historical background to the rise of visual writing is used as a backdrop to the semiotic analysis of the emoji phenomenon. The way we read and write messages today with visual elements such as emoji may indicate a radical shift away from a linear mode of processing information, as imprinted in alphabetic forms of writing, toward a more holistic and imaginative mode. However, because emoji usage and creativity depend on specific technologies, it remains to be seen if such writing can survive as technologies change. The main argument in this paper is that emojis are more part of parole than they are a separate langue, but they nonetheless reveal changes that the latter is undergoing in an age of digital multimodal communication.
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Sampietro, Agnese. "Cómo hacer palabras con emojis: sustitución y enfatización visual de vocablos en WhatsApp." Revista Estudios del Discurso Digital (REDD), no. 2 (December 11, 2019): 1–33. http://dx.doi.org/10.24197/redd.2.2019.1-33.
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En este trabajo se estudia un uso muy peculiar de los emojis en la aplicación WhatsApp: la sustitución o reproducción de un término por medio de su representación visual. A través de un procedimiento cualitativo, se analiza un corpus de mensajes de WhatsApp, identificando regularidades tanto en el uso de los emojis para sustituir o enfatizar palabras, como los posibles mecanismos de trasposición visual. Los emojis pueden reemplazar o repetir visualmente sustantivos, verbos, adjetivos, interjecciones y expresiones más complejas. A falta de un emoji específico, los usuarios recurren a aproximaciones en general metonímicas al término buscado o a referencias al imaginario colectivo. También se observa que los emojis reproducen estereotipos y sesgos presentes en nuestra sociedad.
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Chen, Zhenpeng, Yanbin Cao, Huihan Yao, Xuan Lu, Xin Peng, Hong Mei, and Xuanzhe Liu. "Emoji-powered Sentiment and Emotion Detection from Software Developers’ Communication Data." ACM Transactions on Software Engineering and Methodology 30, no. 2 (March 2021): 1–48. http://dx.doi.org/10.1145/3424308.
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Sentiment and emotion detection from textual communication records of developers have various application scenarios in software engineering (SE). However, commonly used off-the-shelf sentiment/emotion detection tools cannot obtain reliable results in SE tasks and misunderstanding of technical knowledge is demonstrated to be the main reason. Then researchers start to create labeled SE-related datasets manually and customize SE-specific methods. However, the scarce labeled data can cover only very limited lexicon and expressions. In this article, we employ emojis as an instrument to address this problem. Different from manual labels that are provided by annotators, emojis are self-reported labels provided by the authors themselves to intentionally convey affective states and thus are suitable indications of sentiment and emotion in texts. Since emojis have been widely adopted in online communication, a large amount of emoji-labeled texts can be easily accessed to help tackle the scarcity of the manually labeled data. Specifically, we leverage Tweets and GitHub posts containing emojis to learn representations of SE-related texts through emoji prediction. By predicting emojis containing in each text, texts that tend to surround the same emoji are represented with similar vectors, which transfers the sentiment knowledge contained in emoji usage to the representations of texts. Then we leverage the sentiment-aware representations as well as manually labeled data to learn the final sentiment/emotion classifier via transfer learning. Compared to existing approaches, our approach can achieve significant improvement on representative benchmark datasets, with an average increase of 0.036 and 0.049 in macro-F1 in sentiment and emotion detection, respectively. Further investigations reveal that the large-scale Tweets make a key contribution to the power of our approach. This finding informs future research not to unilaterally pursue the domain-specific resource but try to transform knowledge from the open domain through ubiquitous signals such as emojis. Finally, we present the open challenges of sentiment and emotion detection in SE through a qualitative analysis of texts misclassified by our approach.
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Tommi, Tommi, Acep Iwan Saidi, Thirathep Chonmaitree, Mohamed Razeef Abdul Razak, and Wegig Murwonugroho. "Humanization of Logo as a Representation of Social Values in Halodoc." JSW (Jurnal Sosiologi Walisongo) 6, no. 1 (April 30, 2022): 43–58. http://dx.doi.org/10.21580/jsw.2022.6.1.9520.
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In utilizing the Halodoc application, there is a communication gap between direct speech communication and communication through the application. Through Roland Barthes' semiotic method, this research attempts to examine this problem and propose an alternative solution in the form of emoji humanization. Heidy's emoji structure is indeed synonymous with the Halodoc logo. Meanwhile, according to the connotative analysis, you can see the emoji visualization whose characters are identical to today's human characters. This character is characterized by expressions and facial expressions that look cheerful and friendly. This study concludes that there are a number of indicators of success in composing humanist emojis and still referencing the main logo identity. In the principle of emoji design, structurally it must be dominated by a shape similar to the original logo. The addition of mimics, expressions, limb movements, and body movements itself must represent the true expressions of humans who provide health ordering services. Thus, emojis are more attractive, interactive, and communicative. As confirmed by various studies, this intimacy between users and emojis that looks humanist has proven to strengthen customer trust in services.
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Hauthal, Eva, Alexander Dunkel, and Dirk Burghardt. "Emojis as Contextual Indicants in Location-Based Social Media Posts." ISPRS International Journal of Geo-Information 10, no. 6 (June 12, 2021): 407. http://dx.doi.org/10.3390/ijgi10060407.
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The presented study aims to investigate the relationship between the use of emojis in location-based social media and the location of the corresponding post in terms of perceived objects and conducted activities connected to this place. The basis for this is not a purely frequency-based assessment, but a specifically introduced measure called typicality. To evaluate the typicality measure and examine the assumption that emojis are contextual indicants, a dataset of worldwide geotagged posts from Instagram relating to sunset and sunrise events is used, converted to a privacy-aware version based on a Hyperloglog approach. Results suggest that emojis can often provide more nuanced information about user activities and the surrounding environment than is possible with hashtags. Thus, emojis may be suitable for identifying less obvious characteristics and the sense of a place. Emojis are already explored in research, but mainly for sentiment analysis, for semantic studies or as part of emoji prediction. In contrast, this work provides novel insights into the user’s spatial or activity context by applying the typicality measure and therefore considers emojis contextual indicants.
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Al-Rawi, Ahmed, Maliha Siddiqi, Rosemary Morgan, Nimisha Vandan, Julia Smith, and Clare Wenham. "COVID-19 and the Gendered Use of Emojis on Twitter: Infodemiology Study." Journal of Medical Internet Research 22, no. 11 (November 5, 2020): e21646. http://dx.doi.org/10.2196/21646.
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Background The online discussion around the COVID-19 pandemic is multifaceted, and it is important to examine the different ways by which online users express themselves. Since emojis are used as effective vehicles to convey ideas and sentiments, they can offer important insight into the public’s gendered discourses about the pandemic. Objective This study aims at exploring how people of different genders (eg, men, women, and sex and gender minorities) are discussed in relation to COVID-19 through the study of Twitter emojis. Methods We collected over 50 million tweets referencing the hashtags #Covid-19 and #Covid19 for a period of more than 2 months in early 2020. Using a mixed method, we extracted three data sets containing tweets that reference men, women, and sexual and gender minorities, and we then analyzed emoji use along each gender category. We identified five major themes in our analysis including morbidity fears, health concerns, employment and financial issues, praise for frontline workers, and unique gendered emoji use. The top 600 emojis were manually classified based on their sentiment, indicating how positive, negative, or neutral each emoji is and studying their use frequencies. Results The findings indicate that the majority of emojis are overwhelmingly positive in nature along the different genders, but sexual and gender minorities, and to a lesser extent women, are discussed more negatively than men. There were also many differences alongside discourses of men, women, and gender minorities when certain topics were discussed, such as death, financial and employment matters, gratitude, and health care, and several unique gendered emojis were used to express specific issues like community support. Conclusions Emoji research can shed light on the gendered impacts of COVID-19, offering researchers an important source of information on health crises as they happen in real time.
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Khaltar, Narmandakh, and Tsolmon Shirnen. "Exploring Emoji Use and Frequency Among Mongolian Users: Examples from Facebook and Twitter." American Journal of Youth and Women Empowerment 1, no. 1 (November 10, 2022): 30–35. http://dx.doi.org/10.54536/ajywe.v1i1.924.
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Internet linguistics has been rapidly improving since the advent of the Internet; humanity has come to value or emphasize a new form of communication, the Internet, or computer-mediated communication (CMC) around the world. Emoji is a graphical image, representing attitudes or concepts, and emotional feelings in a simple way. Emojis became popular around 2010 worldwide and can be used on any smartphone or computer in a message or conversation. Dresner & Herring stated that some social factors include the gender and the age of CMD users (2010). Emoji is one of people’s emotional and facial expressions, and its use exceeds the standard norm of the language, especially on Facebook and Twitter, known as the most used platforms in Mongolian internet communication. We have studied one of the sociolinguistics studies, the emoji use on Facebook and Twitter in Mongolian computer-mediated discourse, also known as conversational discourse, comparing people’s age, gender, emoji use, and frequency through the questionnaire we processed. The findings of the study show that people write online using excessive emojis, which means that emojis have become an integral part of people’s everyday life. Following excessive use of emojis, there is a fear that may lead to language extinction, and the spelling rules may be compromised, which could adversely affect the official written language. We hope that this study will contribute to the scholarly literature on computer-mediated discourse in general, Mongolian computer-mediated discourse in particular, and the emoji use and its frequency, a recently introduced in our country and a little-studied feature of computer-mediated discourse.
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Hamdan, Hady. "The Communicative Functions of Emojis: Evidence from Jordanian Arabic-Speaking Facebookers." PSYCHOLINGUISTICS 31, no. 1 (January 3, 2022): 141–72. http://dx.doi.org/10.31470/2309-1797-2022-31-1-141-172.
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Purpose. This paper examines the communicative (also known as pragmatic) functions of the most common five emojis in the Jordanian context as perceived by Jordanian Facebook users.
Methods. The data were collected in four stages. First, the researcher shared a post on his Facebook account in which he asked his Jordanian-Arabic speaking virtual friends to report in a comment the most common emojis they use. The researcher compiled 174 comments / responses with 1716 emoji tokens. Second, the received tokens were used to identify the most common five emojis. Third, in order to identify the set of functions of each emoji, the researcher shared another post in which he asked the same previous group to report when each of them tends to press each emoji and for what purposes. Based on the received comments, a preliminary list of functions was prepared. Finally, the proposed functions were subjected to a validation process by two Jordanian-Arabic speaking linguists and three senior students from the Department of English at the University of Jordan. Most of their judgments were compatible with those of the researcher. To further validate the data, the acceptability of the identified functions were tested against the intuition of 261 Jordanian BA students at the University of Jordan.
Results. The findings show that the five most common emojis in the Jordanian context are (1) the Face With Tears of Joy, (2) the Red Heart, (3) the Slightly Smiling Face, (4) the Face Blowing a Kiss, and (5) the Winking Face. Furthermore, emojis are not only used to show emotions, but can also act as markers of illocutionary force, as face saving devices, and as boosters of rapport. The set of emojis examined in this study can be employed to perform 19 multiple illocutionary acts including but not limited to expressive acts (happiness, admiration, etc.), directive acts (e.g, directing the addressee to stop doing something) and declarative acts (e.g., threatening). Emojis are not solely used to convey the functions envisaged by their creators. Instead, with time, emojis start to drift extensively from their semantic import by acquiring a wide spectrum of new illocutions.
Conclusions. The study concludes that although emojis are evolving and developing at a rapid pace, becoming more diverse, pervasive and integral in our daily communications, sharing even some of the characteristics of human language such as arbitrariness, they remain a mode of communication within computer-mediated communication (CMC). At this stage, they can mainly play the role of non-verbal cues that help us understand the intended message and function as a parallel lingua franca limited in domains of CMC.
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Jeon, Hye-Jin. "The Mechanism of Empathy and Relationship Commitment Through Emojis: Path to Perspective Taking, Inner Imitation, Emotional Empathy, and Relationship Commitment." SAGE Open 10, no. 4 (October 2020): 215824402096967. http://dx.doi.org/10.1177/2158244020969675.
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We analyzed empathy and relationship commitment mechanisms through emojis. We defined emojis based on theoretical reviews and neuroscientific studies as a mind reading process. Perspective taking, inner imitation, and emoji cognition were independent variables. Emotional empathy and emotional response was the mediating variable. Relationship commitment and behavioral response was the dependent variable. Analyzing the relationship between variables indicated emotional empathy and relationship commitment through emojis having positive (+) relationships with “perspective taking” and “inner imitation,” the two dimensions of mind reading (cognitive and emotional) and, among them, a stronger positive (+) relationship with inner imitation, which is simulation theory’s (ST) cognitive process. Relationship commitment through emojis was strongly related to emotional empathy as a mediating factor than being directly related to cognitive processes (perspective taking, inner imitation). Moreover, considering inner imitation’s influence being greater than perspective taking, relationship commitment through emojis is mainly caused by emotional empathy with inner imitation as a mediating factor.
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Sampietro, Agnese, Samuel Felder, and Beat Siebenhaar. "Do you kiss when you text? Cross-cultural differences in the use of the kissing emojis in three WhatsApp corpora." Intercultural Pragmatics 19, no. 2 (March 30, 2022): 183–208. http://dx.doi.org/10.1515/ip-2022-2002.
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Abstract Emojis are pictographs added to messages on social media and websites. Researchers have observed that emojis representing kissing faces are often used to close instant messaging conversations. This has been interpreted as an imitation of cheek kissing, a common behavior in some cultural contexts. We analyze the use of seven types of kissing emojis in three corpora of WhatsApp chats, one from Spain (where cheek kisses in face-to-face interaction are commonplace in many situations), the other from Germany (where kisses are occasionally given), and the third from the German-speaking part of Switzerland (where cheek kisses are a common greeting between relatives and friends). To do so, we systematically categorize and compare the use of a sample of these emojis on WhatsApp. The analysis suggests that there are differences between the three corpora in the use of the kissing emojis. The emoji “face throwing a kiss” is often included in closing messages in the Spanish and Swiss-German data, while in the Federal German corpus kisses do not appear at the end of a conversation; using these emojis in openings is uncommon in all three corpora. This suggests that these emojis can exhibit cultural variation, but they do not clearly mirror face-to-face behavior.
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Cantamutto, Lucía, and Cristina Vela Delfa. "¿De qué color es tu corazón? El uso de emojis en los procesos de activismo social." Revista Dígitos 1, no. 6 (April 16, 2020): 119. http://dx.doi.org/10.7203/rd.v1i6.183.
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En este artículo se analiza el empleo de los emojis como elemento de afiliación grupal en los procesos de activismo digital. A partir de la observación de diferentes perfiles activos en la red social Twitter y de tuits producidos por dichas cuentas, se identifica el uso de los emoji del corazón (en distintos colores) en concurrencia con diferentes hashtag como estrategias de encuadre. En este trabajo exploratorio, ilustramos nuestro estudio con la oposición que, entre el emoji del corazón verde y el emoji del corazón azul, se generó en Twitter, a partir de la remediación digital de los pañuelos de colores empleados por las y los activistas movilizados en torno a la discusión sobre la ampliación de los supuestos de la ley del aborto que se llevó a cabo en Argentina, en junio de 2018, y en otros países de Latinoamérica. De la misma forma que estos pañuelos conformaban insignias identificativas en las movilizaciones callejeras, los emojis de colores se han convertido en señas de identidad en la interacción digital. Los resultados exponen que los colores de los emojis de corazón coinciden con determinados hashtag y, de manera conjunta, permiten manifestar la afiliación ideológica/política del usuario y del contenido generado. Esta función novedosa de los emojis es una estrategia propia de la dinámica del estilo electrónico.
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Gantiva, Carlos, Andrés Zarabanda, Jenny Ricaurte, Luz Calderón, Katherine Ortiz, and Karen Castillo. "Efecto de la empatía afectiva sobre el procesamiento cortical de emojis." Pensamiento Psicológico 17, no. 1 (March 23, 2019): 7–17. http://dx.doi.org/10.11144/javerianacali.ppsi17-1.eeap.
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Objetivo. Identificar las diferencias en el procesamiento cortical de emojis en personas con alta y baja empatía afectiva. Método. El estudio se llevó a cabo con 69 participantes, distribuidos en dos grupos –baja y alta empatía afectiva–, según su puntaje en el Índice de Reactividad Interpersonal. Cada participante observó emojis con expresiones de alegría, ira y neutros. Se registraron los potenciales relacionados a eventos (PRE) P100, N170 y LPP. Resultados. Se encontró una mayor amplitud del N170 en el grupo de personas con alta empatía afectiva y, en general, mayor magnitud del LPP ante emojis de ira. Conclusión. Los resultados sugieren que los emojis son procesados corticalmente de forma similar al rostro humano y que la empatía afectiva modula la codificación del emoji, pero no la atención temprana y el enganche atencional hacia estos estímulos.
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Atif, Muhammad, and Valentina Franzoni. "Tell Me More: Automating Emojis Classification for Better Accessibility and Emotional Context Recognition." Future Internet 14, no. 5 (May 5, 2022): 142. http://dx.doi.org/10.3390/fi14050142.
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Users of web or chat social networks typically use emojis (e.g., smilies, memes, hearts) to convey in their textual interactions the emotions underlying the context of the communication, aiming for better interpretability, especially for short polysemous phrases. Semantic-based context recognition tools, employed in any chat or social network, can directly comprehend text-based emoticons (i.e., emojis created from a combination of symbols and characters) and translate them into audio information (e.g., text-to-speech readers for individuals with vision impairment). On the other hand, for a comprehensive understanding of the semantic context, image-based emojis require image-recognition algorithms. This study aims to explore and compare different classification methods for pictograms, applied to emojis collected from Internet sources. Each emoji is labeled according to the basic Ekman model of six emotional states. The first step involves extraction of emoji features through convolutional neural networks, which are then used to train conventional supervised machine learning classifiers for purposes of comparison. The second experimental step broadens the comparison to deep learning networks. The results reveal that both the conventional and deep learning classification approaches accomplish the goal effectively, with deep transfer learning exhibiting a highly satisfactory performance, as expected.
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Lee, Jungwoo, Cheong Kim, and Kun Chang Lee. "Investigating the Negative Effects of Emojis in Facebook Sponsored Ads for Establishing Sustainable Marketing in Social Media." Sustainability 13, no. 9 (April 26, 2021): 4864. http://dx.doi.org/10.3390/su13094864.
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Emojis are prevalent in modern social media advertising. Despite this fact, little research can be found on its effects on consumer purchase intentions. This study seeks to examine purchase intentions in the context of Sponsored Ads on Facebook News Feeds, their perceived intrusiveness, and how the added factor of emoji presence can further affect consumer perception in order to suggest a pathway for establishing sustainable marketing strategies. We investigated the effect of emojis on consumers and then the extent to which ad personalization can attenuate intrusiveness to the point of influencing purchase intentions. In the empirical investigations (an online study) conducted, the study revealed several interesting findings. First, the emoji presence in Sponsored Ads on the News Feed did not prompt the users’ perceived intrusiveness. Second, the emoji use led to decreased purchase intentions. Third, the perceived intrusiveness did not mediate the relationship between emoji presence (vs. absence) and purchase intentions. Lastly, the emoji presence decreased perceived intrusiveness and also increased purchase intentions when consumers perceived ads to be less personalized. The findings of this research provide both theoretical and managerial implications of the effects of emojis, and the reasons as to why their usage affects the desired ad goals when used in Sponsored Ads on Facebook from the perspective of sustainable marketing.
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Zhou, Yuhang, and Wei Ai. "#Emoji: A Study on the Association between Emojis and Hashtags on Twitter." Proceedings of the International AAAI Conference on Web and Social Media 16 (May 31, 2022): 1169–80. http://dx.doi.org/10.1609/icwsm.v16i1.19367.
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Prevalent on modern social media, both hashtags and emojis are text elements that function beyond plain text. While hashtags utilize free-formed strings and are highlighted by the platform, emojis are bonded by Unicode Standard and rendered by the platforms. Yet both are used to mark discussion topics, express sentiment, show identity, and highlight keywords. This paper analyzes and highlights the strong association between hashtags and emojis, not only in their usage frequency, but also in their semantics. We show that the association is strong enough for improving downstream tasks. To this end, we design a representation learning model that can learn emoji-based representations to improve hashtag prediction.
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Moussa, Salim. "An emoji-based metric for monitoring consumers’ emotions toward brands on social media." Marketing Intelligence & Planning 37, no. 2 (April 1, 2019): 211–25. http://dx.doi.org/10.1108/mip-07-2018-0257.
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PurposeThe purpose of this paper is to introduce and test a new emoji-based metric that could be used to monitor consumers’ emotions toward brands on social media.Design/methodology/approachTo test this new metric, 720 consumer tweets were retrieved from official Twitter accounts of 18 leading global brands representing 6 product categories/markets. In order to check its validity, the emoji-based metric was correlated with two measures: the percentage of positive emojis from Brandwatch’s (2018) Emoji Report and the American Customer Satisfaction Index (ACSI) for 2017.FindingsThe findings of this paper indicate that consumers tend to use more (vs less) positive emojis when expressing their feelings toward Coca-Cola (vs Taco Bell). They also show that the new metric is highly and positively associated with the ACSI, hence supporting its validity.Research limitations/implicationsThe new metric is only applicable to brands that have a social media presence.Practical implicationsThe proposed metric is easy to implement and interpret by almost every researcher and manager.Originality/valueWhile all extant brand sentiment analyses focus on analyzing the words in brand-related user-generated content, this paper considers an alternative source of information about emotions, that is, emojis. Beyond being valid, the proposed emoji-based metric is unique, easy to implement and interpret, and generalizable.
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Graham, Sage L. "A wink and a nod: The role of emojis in forming digital communities." Multilingua 38, no. 4 (July 26, 2019): 377–400. http://dx.doi.org/10.1515/multi-2018-0037.
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Abstract As digital interactions become more global, individuals who bring divergent practices ‘to the keyboard’ must interact with other participants who come to the digital space with different cultural norms and expectations. This study explores the interface between local expectations and global practice through emoji use in online gaming – a venue which brings people from around the globe together on a common ‘playing field’. Since emojis were originally designed to tap into universals in human experience and expression, they are a ready-made resource through which individuals can integrate their culture-based expectations with communicative norms that are rooted in the common denominators of the (global) digital environment. Using live chat data from the game streaming platform Twitch, this study examines emojis posted to the open chat room during game streams of one female and one male gamer. The analysis examines the ways that participants use these semiotic images to orient toward gaming communities of practice and claim identities within gaming groups. It also explores whether emoji use is affected by the gender of the streamer. Analysis indicates that participants in the man’s stream differ from participants woman’s stream in the ways they use emojis to claim community membership and employ emojis as phatic devices.
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Danesi, Marcel. "The Law and Emojis: Emoji Forensics." International Journal for the Semiotics of Law - Revue internationale de Sémiotique juridique 34, no. 4 (July 23, 2021): 1117–39. http://dx.doi.org/10.1007/s11196-021-09854-6.
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Amer, Mohamed Mahrous Mahrous, Yvonne Hwei-Syn Kam, and Aiman Hussein Elkhedrawi. "Improving memorability using Emojis in a shoulder surfing resistant authentication method." F1000Research 11 (March 29, 2022): 362. http://dx.doi.org/10.12688/f1000research.73691.1.
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Background: Emojis are icons that are familiar and fun to add pizzazz and colour to communication. They have also been used in authentication where the emojis form memorable pictogram story-like passwords. Emojis, which are graphical, are in general vulnerable to shoulder surfing attacks (SSAs). This paper studies whether graphics such as emojis offer better memorability than numerics when implemented in a shoulder-surfing resistant authentication method. Thus, the proposed method aims to meet both needs of being shoulder-surfing resistant as well as being memorable. Methods: In this paper, a SSA resistant method (DragPIN) is used as a reference system on which to implement emojis in place of numerics. Additionally, a new feature, cue questions was implemented for added security. In the proposed method, users composed emoji-based stories using personalised cue questions that served as memory aids. Moreover, these self-chosen cue questions were less comprehensible to shoulder-surfing observers. There were two variants of the DragPIN method, manual and automatic-sliding. To compare the differences, both the reference configuration and modified versions based on the proposed method were implemented. Thirty people participated in user testing. A pre- and post-survey appraised user experience. User testing and survey on both methods and their variants for performance, memorability, and usability were performed. Results: All implementations successfully resisted shoulder surfing. The time taken for login in the manual variant using the proposed methodology was shorter than using the reference method. After four to six weeks, login performance taking into account intermediate failures was better for the proposed method (86.7-91.7%) than the reference method (76.7-78.3%). Hypothesis testing also showed significance in the results. This could point to higher memorability in the proposed method. Conclusion: The study provides testing of emoji-based compared to PIN-based implementation in authentication. Emoji-based stories may form memorable passwords while personalised cue questions may aid memorability.
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Shah, Reena, and Ruchi Tewari. "Mapping Emoji Usage Among Youth." Journal of Creative Communications 16, no. 1 (January 21, 2021): 113–25. http://dx.doi.org/10.1177/0973258620982541.
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Emoji is now a popular inclusion in technology-mediated communication and a part of everyday expression of users. Yet, there is a dearth of scientifically designed research studies focussing on the human implications of the use of emojis. Limited systematic inquiry in this area is restricted to technical studies focussing on algorithm analysis of humongous quantitative data ignoring the people who are posting these emojis. Therefore, in the present study, an attempt is made to study the use of emojis from an individual’s behavioural perspective borrowing from the classic ‘contagion theory’ and the ‘information-signal theory’. A mixed research approach was adopted to study young university student’s emoji usage behaviour. Focus group discussion (FGD) was conducted on 11 participants with an average age of 22.5 years. The discussion was transcribed and thematic analysis was then conducted from which a survey instrument was developed which was administered to 250 university students. These survey data were then analysed using exploratory factor analysis. Results show that social media platforms, linguistic pattern, social relationships, emotional connect and level of formality and gender emerged as important factors that drive emoji usage. The findings of the study indicate the psychological implications and socio-behavioural impact of emoji usage which can be used for creating regulations and norms. What appears to be casual pictorial supplement of textual messages holds the power to be developed as a stand-alone language which could impact the usage of language-dependent communication.
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Yüce, Arif, Volkan Aydoğdu, and Hakan Katırcı. "Common Language of New Era in Sport Clubs: Emojis." Jurnal The Messenger 13, no. 1 (September 25, 2021): 63. http://dx.doi.org/10.26623/themessenger.v13i1.2390.
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<em><span>Defined as an easy and automated way of expressing emotions in the digital age, emojis are emerging as a new language in the social media world and sports clubs also. For sports clubs, it is of vital importance to communicate and establish effective relations with fans or followers. Hence, almost all professional sports clubs use social media and shape their social media accounts to interact with fans/followers and effectively maintain marketing communication efforts.</span></em><span> <em>The aim of this study was to determine the content of emoji usage in tweets of Turkish sports clubs (Besiktas JK, Fenerbahce SK, Galatasaray SK, Istanbul Başakşehir FK, Trabzonspor SK). Since Twitter is one of the most heavily used social media networks of sports clubs, so in this study was preferred</em>. <em>Content analysis method was used to examine emojis used by sports clubs. The study found that sports clubs use emojis that create positive and neutral connotations. Emojis used are heavily determined to be visuals depicting the colors and symbols of sports clubs. The study is the first to examine sports clubs' emojis used. Hence, the study included important results for the management of communication and marketing strategies of sports clubs on social media.</em></span>
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Boender, Tamara Sonia, Noah Louis-Ferdinand, and Gideon Duschek. "Digital Visual Communication for Public Health: Design Proposal for a Vaccinated Emoji." Journal of Medical Internet Research 24, no. 4 (April 7, 2022): e35786. http://dx.doi.org/10.2196/35786.
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In the 21st century, the internet and particularly social media have become essential platforms for the spread of health information (including misinformation and disinformation). One of the distinguishing features of communication on these platforms is the widespread use of emojis. Though seemingly trivial emojis are now used by many if not most public health figures and organizations alongside important health updates. Much of that information has had to do with vaccination. Vaccines are a critical public health tool but one surrounded by falsehoods, phobias, and misinformation fueling vaccine hesitancy. Part of that has to do with their lack of positive representation on social media (eg, the syringe emoji is a plain needle, which for many people is an uncomfortable image). We thus argue that vaccination deserves an entirely new emoji to communicate vaccine confidence and discuss a design proposal for a vaccinated emoji that has gained traction in the global public health community.
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Montenegro Díaz, Denis José. "Características del uso de emojis en la comunicación por el chat de Whatsapp (Characteristics in the use of emojis in the communication through WhatsApp Chat)." HAMUT'AY 5, no. 1 (June 19, 2018): 36. http://dx.doi.org/10.21503/hamu.v5i1.1519.
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La presente investigación tuvo como objetivo general determinar las características del uso de emojis en la comunicación en el chat de Whatsapp, en función de aspectos sociodemográficos, prevalencia de uso e interpretaciones personales. Para tal fin se realizó un análisis estadístico descriptivo cuantitativo, con la finalidad de identificar las principales características manifestadas por usuarios de Whatsapp en el uso de emojis en el chat de conversación. La recolección de datos se llevó a cabo mediante un diseño exploratorio. Con este fin, se aplicó una encuesta web de 22 ítems, validado por juicio de expertos con una valoración promedio 80.90%. La encuesta se difundió en redes sociales entre el 30 de enero al 28 de febrero del 2018. La muestra fue no probabilística, con un total de 222 usuarios de Whatsapp, procedentes de diferentes países, con edad promedio entre 18 a 50 años. Los resultados mostraron que el 56.8% de personas que usaron los emojis en el chat de Whatsapp eran mujeres yel 43.2% varones. Así mismo, se encontró que el 29.7% fueron estudiantes y el 21.2% docentes, todos ellos universitarios. En cuanto al uso de los emojis se halló que los de mayor uso fueron el que llora de risa, el sorprendido, el pensativo, el de ataque de risa y del beso. Las interpretaciones que los usuarios hicieron de los emojis fue muy diversa, puesto que el significado dependió de la asimilación del sentido visual que cada uno de ellos le asignó al emoji.
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Sampietro, Agnese, Dafne Calvo, and Eva Campos. "Los emojis del 8M: su uso en Twitter durante las movilizaciones feministas de 2019." Revista Dígitos 1, no. 6 (April 16, 2020): 137. http://dx.doi.org/10.7203/rd.v1i6.170.
Full textAbstract:
Los emojis se han convertido en un elemento prototípico de la comunicación digital y han atraído considerable atención académica en los últimos años, pero su uso coincidiendo con eventos específicos no ha sido analizado sistemáticamente. El presente trabajo explora el uso de los emojis en Twitter en ocasión de las manifestaciones y huelgas convocadas en España el 8 de marzo (8M), Día Internacional de la Mujer, analizando un corpus de más de medio millón de tuits publicados del 4 al 9 de marzo de 2019.Los resultados muestran que el uso que se hace en Twitter de estos pictogramas alrededor del 8M es bastante diferente del uso general en la red social. Además de no aparecer las reconocidas caritas amarillas, que suelen predominar en Twitter, el emoji más utilizado en el corpus es el corazón de color violeta, que se está convirtiendo en símbolo del ciberactivismo feminista en España. Los emojis que representan gestos o bien se relacionan con la iconografía de la protesta (como el puño en alto) o son simplemente gestos deícticos que enfatizan visualmente enlaces y adjuntos. Se vislumbran incluso patrones en el uso de los emojis que dependen de la ideología, como el uso de la bandera española, prerrogativa del partido Vox y sus simpatizantes. En general, este trabajo muestra que los emojis se usan de forma altamente simbólica en situaciones de relevancia social, convirtiéndose en un instrumento para el discurso feminista en internet.
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Alrumaih, Abdulrahman, Ali Al-Sabbagh, Ruaa Alsabah, Harith Kharrufa, and James Baldwin. "Sentiment analysis of comments in social media." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (December 1, 2020): 5917. http://dx.doi.org/10.11591/ijece.v10i6.pp5917-5922.
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Social media platforms are witnessing a significant growth in both size and purpose. One specific aspect of social media platforms is sentiment analysis, by which insights into the emotions and feelings of a person can be inferred from their posted text. Research related to sentiment analysis is acquiring substantial interest as it is a promising filed that can improve user experience and provide countless personalized services. Twitter is one of the most popular social media platforms, it has users from different regions with a variety of cultures and languages. It can thus provide valuable information for a diverse and large amount of data to be used to improve decision making. In this paper, the sentiment orientation of the textual features and emoji-based components is studied targeting “Tweets” and comments posted in Arabic on Twitter, during the 2018 world cup event. This study also measures the significance of analyzing texts including or excluding emojis. The data is obtained from thousands of extracted tweets, to find the results of sentiment analysis for texts and emojis separately. Results show that emojis support the sentiment orientation of the texts and that texts or emojis cannot separately provide reliable information as they complement each other to give the intended meaning.
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de la Puente, Gabrielle, and Zarina Muhammad. "emoji summaries." Journal of Writing in Creative Practice 13, no. 1 (January 1, 2020): 147–54. http://dx.doi.org/10.1386/jwcp.13.1.147_3.
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The White Pube present the emoji summaries that accompany their exhibition reviews on thewhitepube.com. The emoji summaries are there to replace the quantitative 1–5 star rating that normally heads typical art and film reviews. Rather than claim the same authoritative objectivity, The White Pube writers will respond to the exhibition with three selective emojis to offer a description of their personal experience.
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Padilla, Xose A. "El código emoji: de la interfaz frecuencia-función a la identidad discursiva digital." Círculo de Lingüística Aplicada a la Comunicación 93 (February 9, 2023): 243–57. http://dx.doi.org/10.5209/clac.83394.
Full textAbstract:
El trabajo que aquí presentamos tiene dos objetivos fundamentales. El primero es examinar la relación entre la frecuencia de los emojis y sus funciones, pragmáticas y discursivas. El segundo es investigar cómo la frecuencia de uso y su relación con las mencionadas variables (los significados trasmitidos o expresados por las mismas) pueden aportar información relevante sobre la ‘identidad discursiva digital’ de los usuarios. Los resultados del análisis estadístico indican que un emoji aparecerá más frecuentemente, de manera significativa, si representa un elemento no verbal; es usado para mitigar posibles conflictos; expresa ironía y humor; es repetible; y puede ser utilizado tanto por mujeres como por hombres (unisex). En relación con la identidad discursiva digital, es posible señalar que hombres y mujeres utilizan indistintamente aquellos emojis que tienen como objetivo limar posibles conflictos, potenciar lo común y conseguir que, en los chats, se produzca un ambiente cortés, divertido y agradable (condición necesaria). Los hombres, sin embargo, a diferencia de las mujeres, ven determinada parte de sus elecciones por otras razones sociales como la ‘identidad masculina’. Este factor podría explicar, por una parte, un uso menor en general de los emojis, quizás por una supuesta atribución de este código a lo femenino; pero, especialmente, ayuda a entender la ausencia de aquellos emojis (tristeza, miedo, súplica, flores, etc.) de cuyo uso pudiera inferirse algún tipo de debilidad, relacionada hipotéticamente con una ‘identidad femenina’.
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Li, Mengdi, Eugene Ch’ng, Alain Yee Loong Chong, and Simon See. "Multi-class Twitter sentiment classification with emojis." Industrial Management & Data Systems 118, no. 9 (October 15, 2018): 1804–20. http://dx.doi.org/10.1108/imds-12-2017-0582.
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Purpose Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been conducted on the multi-class sentiment analysis of tweets. The purpose of this paper is to consider the popularity of emojis on Twitter and investigate the feasibility of an emoji training heuristic for multi-class sentiment classification of tweets. Tweets from the “2016 Orlando nightclub shooting” were used as a source of study. Besides, this study also aims to demonstrate how mapping can contribute to interpreting sentiments. Design/methodology/approach The authors presented a methodological framework to collect, pre-process, analyse and map public Twitter postings related to the shooting. The authors designed and implemented an emoji training heuristic, which automatically prepares the training data set, a feature needed in Big Data research. The authors improved upon the previous framework by advancing the pre-processing techniques, enhancing feature engineering and optimising the classification models. The authors constructed the sentiment model with a logistic regression classifier and selected features. Finally, the authors presented how to visualise citizen sentiments on maps dynamically using Mapbox. Findings The sentiment model constructed with the automatically annotated training sets using an emoji approach and selected features performs well in classifying tweets into five different sentiment classes, with a macro-averaged F-measure of 0.635, a macro-averaged accuracy of 0.689 and the MAEM of 0.530. Compared to those experimental results in related works, the results are satisfactory, indicating the model is effective and the proposed emoji training heuristic is useful and feasible in multi-class TSA. The maps authors created, provide a much easier-to-understand visual representation of the data, and make it more efficient to monitor citizen sentiments and distributions. Originality/value This work appears to be the first to conduct multi-class sentiment classification on Twitter with automatic annotation of training sets using emojis. Little attention has been paid to applying TSA to monitor the public’s attitudes towards terror attacks and country’s gun policies, the authors consider this work to be a pioneering work. Besides, the authors have introduced a new data set of 2016 Orlando Shooting tweets, which will be made available for other researchers to mine the public’s political opinions about gun policies.
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Riordan, Monica A. "Emojis as Tools for Emotion Work: Communicating Affect in Text Messages." Journal of Language and Social Psychology 36, no. 5 (April 11, 2017): 549–67. http://dx.doi.org/10.1177/0261927x17704238.
Full textAbstract:
Emojis are pictures commonly used in texting. The use and type of emojis has increased in recent years; particularly emojis that are not faces, but rather objects. While prior work on emojis of faces suggest their primary purpose is to convey affect, few have researched the communicative purpose of emojis of objects. In the current work, two experiments assess whether emojis of objects also convey affect. Different populations of participants are shown text messages with or without different emojis of objects, asked to rate the message’s affective content, and indicate their confidence in their ratings. Overall results suggest that emojis of objects communicate positive affect, specifically joy. These findings are framed in the sociological theory of emotion work, suggesting that the time and effort involved in using emojis may help maintain and enhance social relationships.
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Lu, Yuehua, and Jiahao Wu. "An Empirical Study on the Use of Emojis by College Students From the Perspective of Symbolic Interactionism." Theory and Practice in Language Studies 12, no. 4 (April 2, 2022): 707–14. http://dx.doi.org/10.17507/tpls.1204.11.
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The present paper, by referring to the theory of Symbolic Interactionism, through the questionnaire survey among college students, studies the functions and influences of emoji use in online communication. It is found that emojis have linguistic, social and aesthetic functions. However, it also has certain disadvantages and limitations.