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Relevant bibliographies by topics / Emoji lexicon

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Academic literature on the topic 'Emoji lexicon'

Author: Grafiati

Published: 11 December 2022

Last updated: 26 January 2023

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Journal articles on the topic "Emoji lexicon"

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Kulikov, Leonid Vasil'evich, Yuliya Viktorovna Potapova, Arina Yur'evna Malenova A Yu, Ivan Stanislavovich Blekanov, and Egor Sergeevich Razumilov. "The peculiarities of using emoji pictograms in online communities with different frequency of use of obscene lexicon." Психолог, no. 1 (January 2022): 1–18. http://dx.doi.org/10.25136/2409-8701.2022.1.37235.

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The subject of this research is the use of pictograms for expressing emotions and feelings in network communication. The object is the comments in several communities in the popular among youth social network VKontakte. The goal of this article lies in the comparison of preferred emoji used by the users to express their emotions and feelings, who are part of the communities with different frequency of use of obscene lexicon. The hypothesis is advanced that the groups with different frequency of use of obscene lexicon differ in their emotional tonality and the emoji pictograms used for expressi

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Chen, Zhenpeng, Yanbin Cao, Huihan Yao, et al. "Emoji-powered Sentiment and Emotion Detection from Software Developers’ Communication Data." ACM Transactions on Software Engineering and Methodology 30, no. 2 (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

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Fauziah, Yuli, Bambang Yuwono, and Agus Sasmito Aribowo. "Lexicon Based Sentiment Analysis in Indonesia Languages : A Systematic Literature Review." RSF Conference Series: Engineering and Technology 1, no. 1 (2021): 363–67. http://dx.doi.org/10.31098/cset.v1i1.397.

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This systematic literature review aims to determine the trend of lexicon based sentiment analysis research in Indonesian Language in the last two years. The focus of the study is on the understanding of preprocessing used in lexicon-based sentiment analysis studies in the last two years, the lexicon used in these studies, and classification accuracy. The main question in this SLR : what techniques of lexicon based sentiment analysis will provide the highest accuracy. The most widely used preprocessing methods in previous research are tokenization, case conversion, stemming, remove punctuation,

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Wahyuni, Rinda, and Indra Budi. "Combining Linguistic, Semantic and Lexicon Feature for Emoji Classification in Twitter Dataset." Procedia Computer Science 135 (2018): 194–201. http://dx.doi.org/10.1016/j.procs.2018.08.166.

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Bansal, Barkha, and Sangeet Srivastava. "Lexicon-based Twitter sentiment analysis for vote share prediction using emoji and N-gram features." International Journal of Web Based Communities 15, no. 1 (2019): 85. http://dx.doi.org/10.1504/ijwbc.2019.098693.

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Srivastava, Sangeet, and Barkha Bansal. "Lexicon Based Twitter Sentiment Analysis for Vote Share Prediction Using Emoji and N-gram Features." International Journal of Web Based Communities 15, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijwbc.2019.10018048.

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Wook, Muslihah, Sharmelen Vasanthan, Suzaimah Ramli, Noor Afiza Mat Razali, Nor Asiakin Hasbullah, and Norulzahrah Mohd Zainudin. "Exploring Students’ Feedback in Online Assessment System Using Opinion Mining Technique." International Journal of Information and Education Technology 10, no. 9 (2020): 664–68. http://dx.doi.org/10.18178/ijiet.2020.10.9.1440.

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Opinion mining has been widely used in recent online reviews or feedback due to its ability to analyse text-based data. The use of this technique for analysing data from students’ feedback needs to be addressed, since most educational institutions are focusing more on questionnaires based on the Likert-scale rather than on the open-review type. To this end, there is a lack of online assessment systems that could automatically analyse open-review questionnaires. Therefore, the main aim of this study is to analyse students’ feedback in an online assessment system through the opinion mining techn

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Phan, Wei Ming Jonathan, Rachel Amrhein, James Rounds, and Phil Lewis. "Contextualizing Interest Scales With Emojis: Implications for Measurement and Validity." Journal of Career Assessment 27, no. 1 (2017): 114–33. http://dx.doi.org/10.1177/1069072717748647.

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The affective nature of emojis makes them suited for anchoring scales to measure the affective preferences of vocational interest. In Study 1, we conducted a content analysis to identify the five images that best represent a bipolar continuum from strongly like to strongly dislike. In Study 2, we compared the psychometric properties of traditional lexical anchors to those of the emoji anchors identified in Study 1 and tested the predictive validity of emoji-anchored scales. Results show emoji-anchored scales possess similar psychometric properties as lexical-anchored scales. Importantly, the i

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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 (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 thes

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Murthy, Dhiraj, Sabitha Sudarshan, Jung-Ah Lee, et al. "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 (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 o

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Dissertations / Theses on the topic "Emoji lexicon"

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Mahmoudi, Nader. "Mining social media as a measure of equity market sentiment." Thesis, 2020. http://hdl.handle.net/1959.13/1428875.

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Research Doctorate - Doctor of Philosophy (PhD)<br>Investor sentiment is an important topic in behavioural finance where endogeneity and spurious correlation are critical issues given unequivocal measures of investor sentiment are not available. Measures of investor sentiment employed in empirical work are estimated usually as market-level proxies that are invariant across individual firms. These measures are not appropriate when empirical issues involve firm-specific issues such a mergers and acquisitions (M&A). Properly constructed measures of sentiment should capture the beliefs of individu

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Books on the topic "Emoji lexicon"

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Morson, Sian. The Age of Emoji: Creating the Lexicon of Mobile Communication. Apress, 2022.

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Book chapters on the topic "Emoji lexicon"

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Zhang, Mingrui “Ray”, Alex Mariakakis, Jacob Burke, and Jacob O. Wobbrock. "A Comparative Study of Lexical and Semantic Emoji Suggestion Systems." In Diversity, Divergence, Dialogue. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71292-1_20.

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Conference papers on the topic "Emoji lexicon"

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Kimura, Mayu, and Marie Katsurai. "Automatic Construction of an Emoji Sentiment Lexicon." In ASONAM '17: Advances in Social Networks Analysis and Mining 2017. ACM, 2017. http://dx.doi.org/10.1145/3110025.3110139.

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Kimura, Mayu, and Marie Katsurai. "Investigating the Consistency of Emoji Sentiment Lexicons Constructed Using Different Languages." In iiWAS2018: 20th International Conference on Information Integration and Web-based Applications & Services. ACM, 2018. http://dx.doi.org/10.1145/3282373.3282417.

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Barbieri, Francesco, and Jose Camacho-Collados. "How Gender and Skin Tone Modifiers Affect Emoji Semantics in Twitter." In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics. Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/s18-2011.

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