To see the other types of publications on this topic, follow the link: Hashtag.
Journal articles on the topic 'Hashtag'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Hashtag.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Adamska, Karolina. "Hashtag, czyli komunikat? Rola i funkcje hashtagów na Twitterze." Studia Medioznawcze 3 (December 11, 2020): 61–70. http://dx.doi.org/10.33077/uw.24511617.ms.2015.62.525.
Full textAbstract:
Artykuł omawia zagadnienie hashtagu jako nowego modelu komunikacyjnego. Autorka wyjaśnia, czym jest hashtag i jakie są jego funkcje. Podaje przykłady zastosowania hashtagów – zarówno ich wady, jak i zalety. Ponadto opisuje znaczenie hashtagów w komunikacji międzynarodowej i międzykulturowej oraz przedstawia podział hashtagów na kategorie tematyczne. W artykule znaleźć można także wiele przykładów zastosowania hashtagów w komunikacji.
2
Habibi, Muhammad, Adri Priadana, and Muhammad Rifqi Ma'arif. "Hashtag Analysis of Indonesian COVID-19 Tweets Using Social Network Analysis." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 15, no. 3 (July 31, 2021): 275. http://dx.doi.org/10.22146/ijccs.61626.
Full textAbstract:
Social media has become more critical for people to communicate about the pandemic of COVID-19. In social media, hashtags are social annotations which often used to denote message content. It serves as an intuitive and flexible tool for making huge collections of posts searchable on Twitter. Through practices of hashtagging, user representations of a given post also become connected. This study aimed to analyze the hashtag of Indonesian COVID-19 Tweets using Social Network Analysis (SNA). We used SNA techniques to visualize network models and measure some centrality to find the most influential hashtag in the network. We collected and analyzed 500.000 public tweets from Twitter based on COVID-19 keywords. Based on the centrality measurement result, the hashtag #corona is a hashtag with the most connection with other hashtags. The hashtag #COVID19 is the hashtag that is most closely related to all other hashtags. The hashtag #corona is the hashtag that most acts as a bridge that can control the flow of information related to COVID-19. The hashtag #coronavirus is the most important of hashtags based on their link. Our study also found that the hashtag #covid19 and #wabah have a substantial relationship with religious-related hashtags based on network visualization.
3
Dempsey Willis, Reilly Anne. "Habermasian utopia or Sunstein's echo chamber? The ‘dark side’ of hashtag hijacking and feminist activism." Legal Studies 40, no. 3 (June 15, 2020): 507–26. http://dx.doi.org/10.1017/lst.2020.16.
Full textAbstract:
AbstractSociety thinks, talks, and communicates in ways which are inherently different now from the pre-Internet era. Hashtags in particular have transformed community formation around a particular topic, issue, or goal. A new and relatively under-studied phenomenon is that of ‘hashtag hijacking’, where individuals or groups use a particular hashtag to draw attention to arguments and narratives which undermine or oppose the hashtag's objective. Most of the current literature looks at hashtag hijacking as a positive outlet for counter-discourse/counter-narratives to challenge dominant groups. This study, however, looks at the ‘dark side’ of hashtag hijacking, where groups use trolling tactics similar to the Alt_Right to reinforce misogynistic views. The hijacking of three hashtags is explored in this study: #notacriminal, #women2drive, and #mydressmychoice, to explore feminist theories on the role of social media in a ‘public space’. Does Twitter function as one common public sphere where inequalities are so deeply embedded that minority voices have no hope of being heard? Or does Twitter function as a meeting place for multiple competing public spheres, thus allowing minority – and in this case feminist – voices to be heard?
4
Burikova, Svetlana A., and Ekaterina Ovchinnikova. "Hashtag as modern text format in linguistics." LAPLAGE EM REVISTA 7, no. 2 (January 7, 2021): 261–68. http://dx.doi.org/10.24115/s2446-6220202172709p.261-268.
Full textAbstract:
Nowadays modern Internet technologies play an important role in our life. The present article deals with the peculiarities of hashtags as new text format used in social network. The article presents characteristic features of hashtag text, classification of hashtag functions, types of hashtags according to their construction and the position of hashtags in the post. Different types of hashtags were subjected to the analysis. Continuous sampling method, descriptive qualitative and quantitative analysis allowed the authors to come to the conclusion about hashtags as linguistic tools. As a result, five hashtag functions and six hashtag types were identified. These findings would help to understand modern online discourse and to prove the idea that hashtags are considered as meaningful elements of social network communication.
5
Saxton, Gregory D., Jerome N. Niyirora, Chao Guo, and Richard D. Waters. "#AdvocatingForChange: The Strategic Use of Hashtags in Social Media Advocacy." Advances in Social Work 16, no. 1 (July 27, 2015): 154–69. http://dx.doi.org/10.18060/17952.
Full textAbstract:
Social media continues to change how advocacy organizations mobilize, educate, and connect with their constituents. One of the most unique yet understudied tools available on social media platforms is the hashtag. Little research exists on how social work and advocacy organizations use hashtags, much less on how such use can be effective. This study examines the hashtag use by 105 constituent members of the National Health Council, a national US-based patient/health advocacy coalition. The study presents an inductive coding scheme of the types of hashtags employed, analyzes inter-sectoral differences in hashtag usage, and examines the relationship between hashtag use and measures of the effectiveness of social media messages.
6
Stilo, Giovanni, and Paola Velardi. "Hashtag Sense Clustering Based on Temporal Similarity." Computational Linguistics 43, no. 1 (April 2017): 181–200. http://dx.doi.org/10.1162/coli_a_00277.
Full textAbstract:
Hashtags are creative labels used in micro-blogs to characterize the topic of a message/discussion. Regardless of the use for which they were originally intended, hashtags cannot be used as a means to cluster messages with similar content. First, because hashtags are created in a spontaneous and highly dynamic way by users in multiple languages, the same topic can be associated with different hashtags, and conversely, the same hashtag may refer to different topics in different time periods. Second, contrary to common words, hashtag disambiguation is complicated by the fact that no sense catalogs (e.g., Wikipedia or WordNet) are available; and, furthermore, hashtag labels are difficult to analyze, as they often consist of acronyms, concatenated words, and so forth. A common way to determine the meaning of hashtags has been to analyze their context, but, as we have just pointed out, hashtags can have multiple and variable meanings. In this article, we propose a temporal sense clustering algorithm based on the idea that semantically related hashtags have similar and synchronous usage patterns.
7
Senussi, Nizar H. "Hashing Out the Hashtag." American Journal of Gastroenterology 112, no. 2 (February 2017): 399–400. http://dx.doi.org/10.1038/ajg.2016.528.
Full text
8
Watson, Ellen. "#Education: The Potential Impact of Social Media and Hashtag Ideology on the Classroom." Research in Social Sciences and Technology 5, no. 2 (May 17, 2020): 40–56. http://dx.doi.org/10.46303/ressat.05.02.3.
Full textAbstract:
Common on social media platforms, the hashtag (#) organizes users’ ideas, emotions, and comments. Originally used to create a searchable platform, the hashtag and its ideology present interesting considerations for changes to education. As students using social media today most certainly use hashtags to converse, hashtag-informed teaching could connect education to students’ worlds instead of forcing students to fit into the pre-defined world of education. Prevalent in post-secondary education, K-12 educators have recently begun to integrate social media tools into their classrooms, but what are the pedagogical implications of the ideologies of these tools? In response, this study asked the following question: “How can the hashtag inform the K-12 classroom?” Using a systematic literature review and thematic analysis, this study analyzed eight articles that discussed the use of hashtags with K-12 students. Findings indicated four themes that could inform the alignment of K-12 classrooms with hashtag ideology: encouraging voice and user-generated content, the potential of self-organization, network hetero/homogeneity, and connecting to space without a common physical space. Suggestions are provided as to how classrooms (and education) may consider restructuring to better reflect hashtag ideology, meeting students in their social media-driven world.
9
Hachaj, Tomasz, and Justyna Miazga. "Image Hashtag Recommendations Using a Voting Deep Neural Network and Associative Rules Mining Approach." Entropy 22, no. 12 (November 30, 2020): 1351. http://dx.doi.org/10.3390/e22121351.
Full textAbstract:
Hashtag-based image descriptions are a popular approach for labeling images on social media platforms. In practice, images are often described by more than one hashtag. Due the rapid development of deep neural networks specialized in image embedding and classification, it is now possible to generate those descriptions automatically. In this paper we propose a novel Voting Deep Neural Network with Associative Rules Mining (VDNN-ARM) algorithm that can be used to solve multi-label hashtag recommendation problems. VDNN-ARM is a machine learning approach that utilizes an ensemble of deep neural networks to generate image features, which are then classified to potential hashtag sets. Proposed hashtags are then filtered by a voting schema. The remaining hashtags might be included in a final recommended hashtags dataset by application of associative rules mining, which explores dependencies in certain hashtag groups. Our approach is evaluated on a HARRISON benchmark dataset as a multi-label classification problem. The highest values of our evaluation parameters, including precision, recall, and accuracy, have been obtained for VDNN-ARM with a confidence threshold 0.95. VDNN-ARM outperforms state-of-the-art algorithms, including VGG-Object + VGG-Scene precision by 17.91% as well as ensemble–FFNN (intersection) recall by 32.33% and accuracy by 27.00%. Both the dataset and all source codes we implemented for this research are available for download, and our results can be reproduced.
10
ÖZŞENLER, Didem. "Digital Activism: An Analysis of #challengeaccepted Hashtag Activism Developed for Violence against Women." WORLD WOMEN STUDIES JOURNAL 6, no. 1 (April 24, 2021): 35–62. http://dx.doi.org/10.46291/wwsj.v6i1.34.
Full textAbstract:
This study includes an analysis conducted in the context of “hashtag activism”, which is one of the digital activism forms. The research was performed on the #challengeaccepted hashtag activist movement that is conducted on Instagram and aims for raising awareness for violence against women. Posts shared by 51 local and foreign women for the #challengeaccepted hashtag activism were selected with the random sampling method. These sampling which is post shared by 51 local and foreign women was chosen by written #challengeaccepted hashtag activism developed for violence against women to the google research motor. The first two news links was chosen and the people who shared these hashtag was chosen and looked their personal instagram pages and added messages. Other hashtags, words, and mottos additional to the #challengeaccepted hashtag were categorized, interpreted, and inferences were made regarding the digital activism by reflecting the details of findings on the conclusion part. These posts that were grouped under specific themes were subjected to both descriptive and content analysis. These themes were created independent of each other and within the context of additional hashtags, date of the post, local-foreign women, support, courage, motivation, power, energy, leadership status. In this study, the concept of digital activism is scrutinized and tried to be analyzed through the social media campaign supported by celebrities in Turkey and around the world with the #challengeaccepted hashtag against violence against women within the concept of social responsibility.
11
Hopke, Jill E., and Molly Simis. "Discourse over a contested technology on Twitter: A case study of hydraulic fracturing." Public Understanding of Science 26, no. 1 (August 2, 2016): 105–20. http://dx.doi.org/10.1177/0963662515607725.
Full textAbstract:
High-volume hydraulic fracturing, a drilling simulation technique commonly referred to as “fracking,” is a contested technology. In this article, we explore discourse over hydraulic fracturing and the shale industry on the social media platform Twitter during a period of heightened public contention regarding the application of the technology. We study the relative prominence of negative messaging about shale development in relation to pro-shale messaging on Twitter across five hashtags (#fracking, #globalfrackdown, #natgas, #shale, and #shalegas). We analyze the top actors tweeting using the #fracking hashtag and receiving @mentions with the hashtag. Results show statistically significant differences in the sentiment about hydraulic fracturing and shale development across the five hashtags. In addition, results show that the discourse on the main contested hashtag #fracking is dominated by activists, both individual activists and organizations. The highest proportion of tweeters, those posting messages using the hashtag #fracking, were individual activists, while the highest proportion of @mention references went to activist organizations.
12
Wuriani, Nur Indah. "AKTIVISME TAGAR #PERCUMALAPORPOLISI SEBAGAI ZEITGEIST DEMOKRASI SIBER DI INDONESIA." WACANA: Jurnal Ilmiah Ilmu Komunikasi 20, no. 2 (December 29, 2021): 171–83. http://dx.doi.org/10.32509/wacana.v20i2.1702.
Full textAbstract:
The uses of hashtag (#) in social media especially Twitter are no longer segmented for building popular conversation related to entertainment topics or trendings. Twitter users actively use hashtags to involve themselves in some political issues, in order to amplify some collective movements or merely to share their opinions and attitudes on specific issues. The concept is known as hashtag activism. Hashtag activism as a part of cyber democracy could only happen in two conditions, when the internet has widely penetrated the society and the uses of social media are becoming more common in the society. This research proposes that hashtag activism is scientifically satisfied four formal properties of cyber democracy's zeitgeist which are duration, scope, course also media and carrier, especially in Indonesia. Through netnography method and the usage Talkwalker, an automatic hashtag analyzer, the research focuses on analyzing the elements of formal properties of Zeitgeist in hashtag #PercumaLaporPolisi on Twitter.
13
Omena, Janna Joceli, Elaine Teixeira Rabello, and André Goes Mintz. "Digital Methods for Hashtag Engagement Research." Social Media + Society 6, no. 3 (July 2020): 205630512094069. http://dx.doi.org/10.1177/2056305120940697.
Full textAbstract:
This article seeks to contribute to the field of digital research by critically accounting for the relationship between hashtags and their forms of grammatization—the platform techno-materialization process of online activity. We approach hashtags as sociotechnical formations that serve social media research not only as criteria in corpus selection but also displaying the complexity of the online engagement and its entanglement with the technicity of web platforms. Therefore, the study of hashtag engagement requires a grasping of the functioning of the platform itself (technicity) along with the platform grammatization. In this respect, we propose the three-layered (3L) perspective for addressing hashtag engagement. The first contemplates potential differences between high-visibility and ordinary hashtag usage culture, its related actors, and content. The second focuses on hashtagging activity and the repurposing of how hashtags can be differently embedded into social media databases. The last layer looks particularly into the images and texts to which hashtags are brought to relation. To operationalize the 3L framework, we draw on the case of the “impeachment-cum-coup” of Brazilian president Dilma Rousseff. When cross-read, the three layers add value to one another, providing also difference visions of the high-visibility and ordinary groups.
14
Рябова, К. О. "English hashtag as an object of linguistic study." Studia Philologica, no. 10 (2018): 66–72. http://dx.doi.org/10.28925/2311-2425.2018.10.9.
Full textAbstract:
The popularity of a hashtag is rising up every day. We use the hashtags to mark our messages or to find the information in the Internet. The hashtag has attracted attention not only Internet users but also scientists. The article focuses on the theoretical background and the approaches to the research of the hashtag as a kind of microtext. The author provides theoretical information about text and microtext, their main characteristics and classification as well as outlines the main linguistic features of the hashtag in the social networks Twitter, Facebook and Instagram. We have considered the etymology of “hashtag” and analyzed the previous works. The article presents the characteristic differences of microtext on phonetic-grapheme, lexical, syntactic levels. It is highlighted variation of pronunciation, graphic and phonetic substitutions, and spelling mistakes. The paper investigates various aspects of using microtext in the social networks.
15
Gerrard, Ysabel. "Beyond the hashtag: Circumventing content moderation on social media." New Media & Society 20, no. 12 (May 28, 2018): 4492–511. http://dx.doi.org/10.1177/1461444818776611.
Full textAbstract:
Social media companies make important decisions about what counts as “problematic” content and how they will remove it. Some choose to moderate hashtags, blocking the results for certain tag searches and issuing public service announcements (PSAs) when users search for troubling terms. The hashtag has thus become an indicator of where problematic content can be found, but this has produced limited understandings of how such content actually circulates. Using pro-eating disorder (pro-ED) communities as a case study, this article explores the practices of circumventing hashtag moderation in online pro-ED communities. It shows how (1) untagged pro-ED content can be found without using the hashtag as a search mechanism; (2) users are evading hashtag and other forms of platform policing, devising signals to identify themselves as “pro-ED”; and (3) platforms’ recommendation systems recirculate pro-ED content, revealing the limitations of hashtag logics in social media content moderation.
16
Zeifer, Barbara. "El hashtag contestatario: cuando los hashtags tienen efectos políticos." Revista Dígitos 1, no. 6 (April 16, 2020): 101. http://dx.doi.org/10.7203/rd.v1i6.178.
Full textAbstract:
El hashtag como elemento discursivo ha sido definido frecuentemente como una etiqueta que identifica el tema de un tuit (#decoración), o una indicación sobre cómo debe ser interpretado (#sorrynotsorry). Sin embargo, cada vez se hacen más frecuentes los hashtags que expresan reclamos y demandas sociales, que dan nombre a nuevos movimientos y colectivos, y que se encuentran inscriptos en las pancartas, banderas y carteles de las manifestaciones populares. Este artículo se propone estudiar en detalle este subtipo de hashtag, que denominaremos “hashtag contestatario”, a partir del análisis de tres casos contemporáneos: #BlackLivesMatter, #JeSuisCharlie y #NiUnaMenos. Los compararemos a partir de elementos tanto de la teoría política y social como del análisis del discurso, y procuraremos concluir con una definición de los hashtag contestatarios.
17
Puspitasari, Devi Ambarwati, and Indah Okitasari. "ANALISIS TINDAK TUTUR BERBASIS KORPUS PADA TAGAR TOLAK OMNIBUS LAW." BAHTERA : Jurnal Pendidikan Bahasa dan Sastra 20, no. 1 (January 14, 2021): 1–14. http://dx.doi.org/10.21009/bahtera.201.01.
Full textAbstract:
ABSTRACT
The purpose of this study is to find out the discursive portrayal of the hashtag “tolakomnibuslaw” on Twitter, which reveals rejection of the Job Creation Law by applying the synergy of linguistic corpus method and illocutionary speech act analysis. The data of this research is a corpus based taken from the utterances of Twitter users who use the hashtag of Omnibus Law Rejection (#tolakomnibuslaw) on October 8, 2020. Word lists and collocations analysis are utilized to see patterns of the hashtag used by people in expressing rejection of the Job Creation Law. Concordance is used to lean more the analysis of speech acts and study the data. The result show that there are 38 styles of the hashtag use. Most of them is the use of noun behind the hashtag “tolakomnibuslaw”. In addition, there are also five common topic hashtags included the hashtag “tolakomnibuslaw”. From the perspective of speech acts, there are five types of speech acts that appear and are dominated by assertive speech and forms of criticism against government effort.
Keywords: linguistic corpus; social media; speech acts
18
Zhang, Yuan, and Hsia-Ching Chang. "Structural Analysis of Medical-Terminology Hashtag versus Lay-Language Hashtag Tweet Collections: An Information Theoretical Method with Entropy Matrix." Data and Information Management 2, no. 3 (December 31, 2018): 153–74. http://dx.doi.org/10.2478/dim-2018-0011.
Full textAbstract:
Abstract Healthcare communication on Twitter is challenging because the space for a tweet is limited, but the topic is too sophisticated to be concise. Comparing medical-terminology hashtags versus lay-language hashtags, this paper explores the characteristics of healthcare hashtags using an entropy matrix which derived from information theory. In this paper, the entropy matrix comprises of six different components used for constructing a tweet and serves as a framework for the structural analysis with the granularity of tweet composition. These granular components include image(s), text with semantic meanings, hashtag(s), @ username(s), hyperlink, and unused space. The entropy matrix proposed in this paper contributes to a new approach to visualizing the complexity level of hashtag collections. In addition, the calculated entropy could be an indicator of the diversity of a user’s choice across those tweet components. Furthermore, the visualizations (radar graph and scatterplot) illustrate statistical structures and the dynamics of the hashtag collections measured by entropy. The results from this study demonstrate a manifest relationship between tweet composition and the number of being retweeted.
19
Fanny, Okta, and Heri Suroyo. "Analysis of Social Media Users Sentiments against Omnibus Law Based on Hashtags on Twitter." SISTEMASI 11, no. 1 (January 9, 2022): 197. http://dx.doi.org/10.32520/stmsi.v11i1.1685.
Full textAbstract:
From the research that has been done, it can be concluded that Sentiment Analysis can be used to know the sentiment of the public, especially Twitter netizens against omnibus law. After the sentiment analysis, it looks neutral artmen with the largest percentage of 55%, then positive sentiment by 35% and negative sentiment by 10%. The results of the analysis showed that the Naïve Bayes Classifier method provides classification test results with accuracy in Hashtag Pro with an average accuracy score of 92.1%, precision values with an average of 94.8% and recall values with an average of 90.7%. While Hashtag Counter For data classification, with an average accuracy value of 98.3%, precision value with an average of 97.6% and recall value with an average of 98.7%. The result of text cloud analysis conducted on a combination of hashtags both Hashtag pros and Hashtags cons, the dominant word appears is Omnibus Law which means that all hashtags in scrap is really discussing the main topic that is about Omnibus Law
20
Oliveira, Jordan Vinícius de. "Hashtag Hashtag Publi?" Revista Vianna Sapiens 10, no. 2 (October 29, 2019): 28. http://dx.doi.org/10.31994/rvs.v10i2.590.
Full textAbstract:
Esta pesquisa visa compreender a prática de publicidade velada em plena sociedade da informação. A teoria das quatro modalidades de intervenção no comportamento humano – lei, sociedade, mercado e arquitetura –, de Lessig, e a técnica de traços de significação, de Babbie, formam o quadro teórico e metodológico. Por meio da análise de disputas relacionadas à identificação publicitária no Conselho de Autorregulamentação Publicitário (CONAR), a questão de pesquisa avalia se a arquitetura própria da web possui elementos internos capazes de incentivar as práticas de publicidade velada. Os principais resultados são assertivos no sentido de afirmar a influência da arquitetura da rede para estimular a ocorrência de tais técnicas escusas de veiculação promocional. Entretanto, constatou-se que este é um fenômeno dinâmico e acompanhado por contramedidas por parte da própria arquitetura da web, bem como das dimensões legais, sociais e de mercado visando coibir a publicidade velada na rede.
21
Fadillah, Dani, and Jian Chang. "The Song #2019GantiPresiden and Political Communication in Simulacra Analysis." Jurnal ASPIKOM 6, no. 2 (July 25, 2021): 292. http://dx.doi.org/10.24329/aspikom.v6i2.935.
Full textAbstract:
This research aims to find out how the hashtag #2019GantiPresiden, which was initially just a common hashtag on Twitter, has triggered a massive mass movement in Indonesia. Moreover, the hashtag incarnated into various souvenirs, even into a song that shouted the need for Indonesia to have a new president. The Hashtag #2019GantiPresiden became a medium of communication to convey political messages from political actors and those interested in the Indonesian presidential elections in 2019. Qualitative method was used in the drafting of this paper by collecting data relating to the topic of discussion and then using the Simulacra logic initiated by Jean Baudrillard in data analysis. The study concluded that in 2019, the #2019GantiPresiden hashtags showed the world that a voice on social media could become a great mass power in the real world.
22
Alsini, Areej, Du Q. Huynh, and Amitava Datta. "Hashtag Recommendation Methods for Twitter and Sina Weibo: A Review." Future Internet 13, no. 5 (May 14, 2021): 129. http://dx.doi.org/10.3390/fi13050129.
Full textAbstract:
Hashtag recommendation suggests hashtags to users while they write microblogs in social media platforms. Although researchers have investigated various methods and factors that affect the performance of hashtag recommendations in Twitter and Sina Weibo, a systematic review of these methods is lacking. The objectives of this study are to present a comprehensive overview of research on hashtag recommendation for tweets and present insights from previous research papers. In this paper, we search for articles related to our research between 2010 and 2020 from CiteSeer, IEEE Xplore, Springer and ACM digital libraries. From the 61 articles included in this study, we notice that most of the research papers were focused on the textual content of tweets instead of other data. Furthermore, collaborative filtering methods are seldom used solely in hashtag recommendation. Taking this perspective, we present a taxonomy of hashtag recommendation based on the research methodologies that have been used. We provide a critical review of each of the classes in the taxonomy. We also discuss the challenges remaining in the field and outline future research directions in this area of study.
23
Pontoh, Andhika Kurniawan. "Computational Propaganda in Hashtag Activism." Jurnal Komunikasi 13, no. 2 (December 7, 2021): 251. http://dx.doi.org/10.24912/jk.v13i2.11086.
Full textAbstract:
The hashtag (#) has an important role in gathering Internet users' support for opinion and value. Computational propaganda has an important role in hashtag activism. This study wants to examine the role of computational propaganda actors such as anonymous political accounts, fake accounts and bot in social media that is able to mobilize the public and also increase the impression of Twitter audiences. The trend of Twitter hashtag activism #BebaskanIBHRS and #NegaraDamaiTanpaFPI began with the arrest of the chairman of the Islamic Defenders Front (FPI) Habib Rizieq Shihab (HRS); the two trending hashtags massively influenced public opinion on Twitter on December 13-14 2020. This study uses a sample of 1000 tweets or conversations on each hashtags and uses Social Network Analysis (SNA) with the Netlytic tool which is able to provide quantitative values of communication networks, through the social network structure of #BebaskaniBHRS and #NegaraDamaiTanpaFPI. This study reveals how the network structure and what factors are carried out by anonymous political actors in carrying out computational propaganda. The results of this study reveal the hashtags activism #BebaskaniBHRS is much more capable of mobilizing the public and is able to generate greater impressions than #NegaraDamaiTanpaFPI. This is because #BebaskaniBHRS has a computational propaganda message in the form of a loaded language with a clear frame and the choice of words directly invites the Twitter public to get involved through a retweet another finding in this research shows computational propaganda movement in hashtag activism was carried out by large groups consisting of anonymous accounts and bot accounts on other side online media coverage about the trending of these hashtag's activism was also able to increasing public attention. Tagar (#) memiliki peran penting dalam mengumpulkan dukungan pengguna Internet terhadap suatu opini dan nilai. Komputasi propaganda memiliki peran penting dalam aktivisme tagar. Penelitian ini ingin mengkaji peran aktor komputasi propaganda seperti akun anonim politik, akun palsu dan bot di media sosial yang mampu memobilisasi publik dan juga meningkatkan kesan khalayak Twitter. Tren aktivisme tagar Twitter #BebaskanIBHRS dan #NegaraDamaiTanpaFPI dimulai dengan penangkapan ketua Front Pembela Islam (FPI) Habib Rizieq Shihab (HRS); kedua tagar yang sedang trending tersebut secara masif memengaruhi opini publik di Twitter pada 13-14 Desember 2020. Penelitian ini menggunakan sampel 1000 tweet atau percakapan pada masing-masing tagar serta menggunakan Social Network Analysis (SNA) dengan alat Netlytic yang mampu memberikan nilai kuantitatif jaringan komunikasi. Melalui struktur jejaring sosial #BebaskaniBHRS dan #NegaraDamaiTanpaFPI, kajian ini mengungkap seperti apa struktur jaringan komunikasi dan hal apa saja yang dilakukan oleh aktor politik anonim dalam melakukan komputasi propaganda. Hasil penelitian ini mengungkapkan bahwa aktivisme tagar #BebaskaniBHRS jauh lebih mampu memobilisasi publik dan mampu menghasilkan impresi yang lebih besar dibandingkan #NegaraDamaiTanpaFPI. Hal ini dikarenakan #BebaskaniBHRS memiliki pesan komputasi propaganda dalam bentuk bahasa yang sarat dengan bingkai yang jelas dan pilihan kata secara langsung mengajak publik Twitter untuk terlibat melalui retweet.Temuan lain dalam penelitian ini menunjukkan gerakan komputasi propaganda dalam aktivisme tagar dilakukan oleh kelompok besar yang terdiri dari akun anonim dan akun bot di sisi lain liputan media daring tentang tren aktivisme tagar ini juga mampu meningkatkan atensi publik.
24
Fadillah, Dani. "HYPER REALITAS SIMULAKRA TAGAR #2019GANTIPRESIDEN DALAM PEMILIHAN PRESIDEN INDONESIA 2019." Profetik: Jurnal Komunikasi 12, no. 2 (March 25, 2020): 249. http://dx.doi.org/10.14421/pjk.v12i2.1669.
Full textAbstract:
This paper is aim to describe how a hashtag appearing in the dynamics of communication on social media is capable of creating a very massive mass movement in the real world. As well as troublesome rulers and authorities to set it up Because it considered a political charge that is in the hashtag could potentially provide a surge of turmoil that is great for the holder of the status quo of the political power of the homeland. By the election of the President of the Republic of Indonesia 2019 was presented with a viral hashtag on social media, the hashtags that were first administered twitted by prosperous Justice Party (Partai Keadilan Sejahtera) politician Mardani Ali Sera, raised the spirit of the masses The number is not minimal not to elect the general election which took place in April 2019. Even until the polls have done, the hashtag still has strong political magic to unite the opposition forces because the reunited was elected to become President of the Republic of Indonesia until 2022. This paper contains the results of qualitative research by making the idea of Jean Baudrillad about Simulacra, simulation, and artificial Phenomenon as his analysis knife. Here the author collects various literary sources in the different news media coverage of the hashtag #2019GantiPresiden then conduct a study of the messages that have a variety of information given to the hashtag Using the turbulent analytical knife of Jean Baudrillad above. Finally, the conclusion of this paper is necessary to fight massive efforts to resist the enormous surge of hashtags #2019GantiPresiden in the homeland in a variety of ways so that the focus is not more significant and to discuss the interests of Political authorities.
25
Uca, Didem. "White Noise and Black Boxes: Social Justice Discourses and Social Media Practices." Seminar: A Journal of Germanic Studies 57, no. 3 (August 1, 2021): 310–18. http://dx.doi.org/10.3138/seminar.57.3.forum004.
Full textAbstract:
Social media has long been a powerful tool for marginalized individuals to connect and form communities. Yet the digital tools used to facilitate these modes of communication, including the hashtag, can also be overpowered by misuse from users outside of these communities. This essay analyzes recent efforts by people of colour in Germany and the US to curate digital spaces by creating and utilizing hashtags such as #BlackLivesMatter and #MeTwo that center their voices, while also discussing appropriation and right-wing responses to progressive social justice activism that threaten the hashtag’s ability to make meaningful content available to the users who need it.
26
Kim, Yunhwan, Donghwi Song, and Yeon Ju Lee. "#Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses." International Journal of Environmental Research and Public Health 17, no. 20 (October 17, 2020): 7550. http://dx.doi.org/10.3390/ijerph17207550.
Full textAbstract:
A dramatic increase has been registered in the number of social media posts in photo form as well as in hashtag activism. Hashtags, which manifest thoughts and feelings clearly and concisely, originated on Twitter, where the length of a post is limited; their use, however, has expanded into other social media services, including Instagram. Hashtags, which make it easy to find and express support for posts of interest, have been widely used for online activism, although they have been criticized for fostering confirmation bias. Moreover, hashtag activism in photo form has been relatively understudied. This research analyzed Instagram photos with antivaccination hashtags as an example of hashtag activism through photos. In addition, we examined how the photo features were related to public response, which was manifested via engagement and comment sentiment. The results suggest that the photos which were categorized into “text” took the largest share. It was also found that the major way of claiming was to imprint key messages that persuade people not to vaccinate with remarks from professionals on photos and provide a source of supporting information in the post text with hashtags of antivaccine intention. Various photo features showed associations with engagement and comment sentiment, but the directions of correlation were usually the opposite: these results suggest that engagement and comment sentiment are separate domains that reveal different public responses.
27
Koster, Ann-Kathrin. "Das radikaldemokratische Moment von Hashtag-Aktivismus." Forschungsjournal Soziale Bewegungen 33, no. 2 (September 11, 2020): 442–56. http://dx.doi.org/10.1515/fjsb-2020-0038.
Full textAbstract:
ZusammenfassungDer Beitrag bietet ausgehend von der politischen Theorie Jacques Rancières eine radikaldemokratische Interpretation von Hashtag-Aktivismus an. Mittelpunkt seiner Demokratietheorie bilden politische Praktiken, welche Exklusionsverhältnisse durch eine demonstrative Anklage zum Gegenstand einer konfliktiven Auseinandersetzung innerhalb der Gesellschaft machen. Ebensolche Prozesse lassen sich mittels einer inhaltlichen Analyse des Hashtags #metwo rekonstruieren, welcher im Sommer 2018 für Aufsehen sorgte. Hashtag-Aktivismus wird so als eine digitale Konstellation erkennbar, die in performativer und pluralistischer Weise den Kampf um Gleichberechtigung und Teilhabe sichtbar werden lässt.
28
Zago, Gabriela Da Silva. "A copa em tweets: análise comparativa do uso das hashtags #EstadaonaCopa e #BairristanaCopa." Rumores 9, no. 18 (December 22, 2015): 270. http://dx.doi.org/10.11606/issn.1982-677x.rum.2015.97385.
Full textAbstract:
<p>Neste trabalho, procuramos analisar e comparar a utilização de hashtags de cobertura no Twitter por um site jornalístico e outro humorístico durante a Copa do Mundo de 2014: o jornal O Estado de S. Paulo, que utilizou a hashtag #EstadaonaCopa para sua cobertura em sites de rede social, e o site satírico O Bairrista, que adotou a hashtag #BairristanaCopa. O estudo foi operacionalizado a partir da combinação de observação com análise de redes sociais como métodos para compreender a estrutura e a dinâmica das redes em torno das respectivas hashtags. Resultados apontam para estruturas de rede semelhantes, porém com dinâmicas diferentes observadas em cada um dos casos estudados.</p>
29
Banbhrani, Santosh Kumar, Bo Xu, Haifeng Liu, and Hongfei Lin. "SC-Political ResNet: Hashtag Recommendation from Tweets Using Hybrid Optimization-Based Deep Residual Network." Information 12, no. 10 (September 22, 2021): 389. http://dx.doi.org/10.3390/info12100389.
Full textAbstract:
Hashtags are considered important in various real-world applications, including tweet mining, query expansion, and sentiment analysis. Hence, recommending hashtags from tagged tweets has been considered significant by the research community. However, while many hashtag recommendation methods have been developed, finding the features from dictionary and thematic words has not yet been effectively achieved. Therefore, we developed an effective method to perform hashtag recommendations, using the proposed Sine Cosine Political Optimization-based Deep Residual Network (SC-Political ResNet) classifier. The developed SCPO is designed by integrating the Sine Cosine Algorithm (SCA) with the Political Optimizer (PO) algorithm. Employing the parametric features from both, optimization can enable the acquisition of the global best solution, by training the weights of classifier. The hybrid features acquired from the keyword set can effectively find the information of words associated with dictionary, thematic, and more relevant keywords. Extensive experiments are conducted on the Apple Twitter Sentiment and Twitter datasets. Our empirical results demonstrate that the proposed model can significantly outperform state-of-the-art methods in hashtag recommendation tasks.
30
Salazar, Eduardo. "Hashtags 2.0 - An Annotated History of the Hashtag and a Window to its Future." Revista ICONO14 Revista científica de Comunicación y Tecnologías emergentes 15, no. 2 (July 1, 2017): 16–54. http://dx.doi.org/10.7195/ri14.v15i2.1091.
Full textAbstract:
Hashtags are an example of a Folksonomy, a term coined by Van der Val in 2004 to designate any label (or “tag”) that helps in the process of indexing and retrieval of online content. That said, the hash (#) symbol has a long heritage throughout the computer age. This paper makes an attempt to trace that history, since the hash was first used as a technology aid and towards its emergence as a new construct, the hashtag. It was first proposed openly by Chris Messina as simple means to “form groups” on Twitter, mirroring, in some ways, the way in which the # symbol was used on IRC (Internet Relay Chat) to designate “channels” themselves associated to specific topics and content exchange. The San Diego bushfires of October 2007 lead to an organic growth in the adoption of hashtags, growth that has not stopped since, making them ubiquitous in the current Internet age. Be as it may, the popularity of the hashtag made it also a vehicle to understand how information flows. Consequently, there is an incredibly rich literature explaining the mechanics of diffusion through social networks, opening, in the process, a new question: is that all for the hashtag? That’s a question we also attempt to answer by introducing a new construct: the “programmable hashtag” (or p#).
31
Zhu, Rui, Delu Yang, and Yang Li. "Learning Improved Semantic Representations with Tree-Structured LSTM for Hashtag Recommendation: An Experimental Study." Information 10, no. 4 (April 6, 2019): 127. http://dx.doi.org/10.3390/info10040127.
Full textAbstract:
A hashtag is a type of metadata tag used on social networks, such as Twitter and other microblogging services. Hashtags indicate the core idea of a microblog post and can help people to search for specific themes or content. However, not everyone tags their posts themselves. Therefore, the task of hashtag recommendation has received significant attention in recent years. To solve the task, a key problem is how to effectively represent the text of a microblog post in a way that its representation can be utilized for hashtag recommendation. We study two major kinds of text representation methods for hashtag recommendation, including shallow textual features and deep textual features learned by deep neural models. Most existing work tries to use deep neural networks to learn microblog post representation based on the semantic combination of words. In this paper, we propose to adopt Tree-LSTM to improve the representation by combining the syntactic structure and the semantic information of words. We conduct extensive experiments on two real world datasets. The experimental results show that deep neural models generally perform better than traditional methods. Specially, Tree-LSTM achieves significantly better results on hashtag recommendation than standard LSTM, with a 30% increase in F1-score, which indicates that it is promising to utilize syntactic structure in the task of hashtag recommendation.
32
Cantini, Riccardo, Fabrizio Marozzo, Giovanni Bruno, and Paolo Trunfio. "Learning Sentence-to-Hashtags Semantic Mapping for Hashtag Recommendation on Microblogs." ACM Transactions on Knowledge Discovery from Data 16, no. 2 (April 30, 2022): 1–26. http://dx.doi.org/10.1145/3466876.
Full textAbstract:
The growing use of microblogging platforms is generating a huge amount of posts that need effective methods to be classified and searched. In Twitter and other social media platforms, hashtags are exploited by users to facilitate the search, categorization, and spread of posts. Choosing the appropriate hashtags for a post is not always easy for users, and therefore posts are often published without hashtags or with hashtags not well defined. To deal with this issue, we propose a new model, called HASHET ( HAshtag recommendation using Sentence-to-Hashtag Embedding Translation ), aimed at suggesting a relevant set of hashtags for a given post. HASHET is based on two independent latent spaces for embedding the text of a post and the hashtags it contains. A mapping process based on a multi-layer perceptron is then used for learning a translation from the semantic features of the text to the latent representation of its hashtags. We evaluated the effectiveness of two language representation models for sentence embedding and tested different search strategies for semantic expansion, finding out that the combined use of BERT ( Bidirectional Encoder Representation from Transformer ) and a global expansion strategy leads to the best recommendation results. HASHET has been evaluated on two real-world case studies related to the 2016 United States presidential election and COVID-19 pandemic. The results reveal the effectiveness of HASHET in predicting one or more correct hashtags, with an average F -score up to 0.82 and a recommendation hit-rate up to 0.92. Our approach has been compared to the most relevant techniques used in the literature ( generative models , unsupervised models, and attention-based supervised models ) by achieving up to 15% improvement in F -score for the hashtag recommendation task and 9% for the topic discovery task.
33
Linabary, Jasmine R., Danielle J. Corple, and Cheryl Cooky. "Feminist activism in digital space: Postfeminist contradictions in #WhyIStayed." New Media & Society 22, no. 10 (October 24, 2019): 1827–48. http://dx.doi.org/10.1177/1461444819884635.
Full textAbstract:
Scholars have argued that digital spaces are key sites for feminist activism, which can be seen in the emergence of “hashtag feminism,” or the use of social media hashtags to address feminist-identified issues through sharing personal experiences of inequality, constructing counter-discourses, and critiquing cultural figures and institutions. However, more empirical research is needed that examines both the possibilities and constraints of hashtag feminism. Through a qualitative analysis of 51,577 archived tweets and semi-structured interviews, we trace the ways #WhyIStayed creates a space for feminist activism in response to victim-blaming related to domestic violence through voice, multivocality, and visibility. More specifically, we critically analyze postfeminist discourses within #WhyIStayed in order to examine contradictions within the hashtag event as well as how these postfeminist contradictions shape possibilities for feminist activism online.
34
Bogolyubova, Olga, Philipp Upravitelev, Anastasia Churilova, and Yanina Ledovaya. "Expression of Psychological Distress on Instagram Using Hashtags in Russian and English: A Comparative Analysis." SAGE Open 8, no. 4 (October 2018): 215824401881140. http://dx.doi.org/10.1177/2158244018811409.
Full textAbstract:
People have been using images to express ideas, share stories, and communicate since early history. The advent of social media has made sharing images an important part of everyday life. Among other things, social networks can be used to express psychological distress; however, research on this topic is limited. The goal of this study was to explore representations of psychological distress in the Russian-speaking segment of Instagram. The study involved contrasting images labeled with hashtags in Russian with images marked by analogous Anglophone hashtags in a data set of 1,512 images. Quantitative content analysis revealed significant differences between images labeled with Russian and Anglophone hashtags. Images containing depictions of texts were significantly less frequent among images with Russian hashtags, while inanimate object depictions were more prevalent. Hashtags for fear in both languages were related not to psychological distress but to the “scary” in popular culture. Images of alcohol were associated with stress hashtags in both languages and with hashtag for depression in Russian only. Images of food were significantly more prevalent among images with Russian hashtag for stress. Current study highlights the need for culturally and linguistically appropriate online mental health interventions.
35
Tariq, Umbreen, Summaira Sarfraz, and Ali Abbas. "Digital media users and Facebook hashtags' misinterpretations." Online Information Review 44, no. 6 (July 16, 2020): 1183–98. http://dx.doi.org/10.1108/oir-08-2019-0262.
Full textAbstract:
PurposeThis paper examines reasons of pragmatic functions' misinterpretation of three types of Facebook hashtags: long, short and multiple mixed hashtags.Design/methodology/approachFocus group interviews of 15 English language learners, who are also active users of Facebook and hashtags, are conducted. Thematic analysis is performed through the software Nvivo for arriving at reliable findings.FindingsThe findings show that unknown vocabulary in contents and lowercasing in long and short hashtags are major factors that cause misinterpretation. Also, the symbol of underscore and appropriate usage of upper and lowercasing of alphabets should be adopted in hashtag writing for the improvement in communication and successful conveyance of the intended meaning.Originality/valueThis paper contributes to the online hashtag writing style by finding reasons for the misinterpretations of different types of hashtags. Hashtags have been developed for adequate communication (Livingstone, 2012), but in Pakistan, hashtags are practiced as a “fashionable” trend and thus result in misinterpretation and inadequate communication among readers even of the same background (Tariq and Sarfraz, 2018). Moreover, this study focuses on the trend of hashtagging that is common among university students and particularly second-language learners because they are active users of Facebook and adopt the latest trends quickly.
36
Berg, Sebastian, Tim König, and Ann-Kathrin Koster. "Political Opinion Formation as Epistemic Practice: The Hashtag Assemblage of #metwo." Media and Communication 8, no. 4 (October 8, 2020): 84–95. http://dx.doi.org/10.17645/mac.v8i4.3164.
Full textAbstract:
The article contributes to the literature on the political use of hashtags. We argue that hashtag assemblages could be understood in the tradition of representing public opinion through datafication in the context of democratic politics. While traditional data-based epistemic practices like polls lead to the ‘passivation’ of citizens, in the digital constellation this tendency is currently challenged. In media like Twitter, hashtags serve as a technical operator to order the discursive fabrication of diverse publicly articulated opinions that manifest in the assemblage of tweets, algorithms and criticisms. We conceptualize such a critical public as an epistemic sensorium for dislocations based on the expression of experienced social imbalances and its political amplification. On the level of opinion formation, this constitutes a process of democratization, allowing for the expression of diverse opinions and issues even under singular hashtags. Despite this diversity, we see a strong tendency of publicly relevant actors such as news outlets to represent digital forms of opinion expression as unified movements. We argue that this tendency can partly be explained by the affordances of networked media, relating the process of objectification to the network position of the observer. We make this argument empirically plausible by applying methods of network analysis and topic modelling to a dataset of 196,987 tweets sampled via the hashtag #metwo that emerged in the German Twittersphere in the summer of 2018 and united a discourse concerned with racism and identity. In light of this data, we not only demonstrate the hashtag assemblage’s heterogeneity and potential for subaltern agency; we also make visible how hashtag assemblages as epistemic practices are inherently dynamic, distinguishing it from opinion polling through the limited observational capacities and active participation of the actors representing its claims within the hybrid media system.
37
Nasution, Nadya Amalia, and Umi Rojiati. "MODERASI BERAGAMA DALAM RUANG DIGITAL: GERAKAN OPINI DIGITAL #SKB3MENTERI." Tatar Pasundan : Jurnal Diklat Keagamaan 15, no. 1 (June 14, 2021): 10–19. http://dx.doi.org/10.38075/tp.v15i1.198.
Full textAbstract:
The study examines Digital Movement of Opinion (DMO) by using hastag #SKB3Menteri hashtags on Twitter, thus forming a mobilization of digital opinion support between actors and hashtags as well as digital opinions. The research data was taken through Netlytic software ranging from February 03, 2021 to February 11, 2021. The method used is Social Network Analysis combined both quantitative and qualitative approach. Quantitatively, the study investigated 2500 samples from communication networks and tweets #SKB3Menteri as many as 3,232. Qualitatively, the researchers analyzed the text which describes social networks related to #SKB3Menteri. The results showed that #SKB3Menteri hashtag creates mobilization with a wide network system. The study also showed the hashtag was able to reach out Twitter users to giving their opinions. Keywords: Religious moderation; Twitter; SKB 3 Ministers; Digital Movement of Opinion; Social Network Analysis
38
De Cock, Barbara, and Andrea Pizarro Pedraza. "From expressing solidarity to mocking on Twitter: Pragmatic functions of hashtags starting with #jesuis across languages." Language in Society 47, no. 2 (March 5, 2018): 197–217. http://dx.doi.org/10.1017/s0047404518000052.
Full textAbstract:
AbstractIn this article, we show how the hashtag #jesuisCharlie, created following the attack on Charlie Hebdo, gave rise to the use of many other hashtags starting with #jesuis, across languages. Through a corpus-based analysis, we show how the meaning of #jesuis broadened from expressing condolence and support following terrorist attacks over expressing condolence for other (violent) deaths to a more general marker of solidarity and alignment. This broadening of meaning is parallel to a formal evolution of the stem jesuis. Moreover, these hashtags have become emblematic of a particular kind of Twitter user. Furthermore, disaligning uses developed, including mocking uses, which disalign both with certain causes (disalignment de re) and with the process of using jesuis as a means of expressing solidarity (disalignment de dicto). Thus, this variety of uses shows that Twitter users exploit the interpersonal possibilities of hashtags to express alignment and disalignment, creating ambient affiliation. (Hashtag, #jesuisCharlie, solidarity, alignment, emblem, mocking, pragmatic functions)*
39
Latushka, Hanna P. "Functional types of hashtags (based on instagram social network)." International Journal “Speech Genres” 17, no. 1 (February 21, 2022): 58–65. http://dx.doi.org/10.18500/2311-0740-2022-17-1-33-58-65.
Full textAbstract:
The space of social networks is improving very quickly, adapting to the needs of society. Until recently, the hashtag on social networks has been more of a tool for organizing and searching posts by topic; but today its function is expanding and deepening; new functions appear that require detailed analysis and description. Moreover, constantly evolving, the hashtag acquires the features of a self-contained text and even goes beyond social networks. In this research, the hashtag on Instagram social network was studied from a linguistic point of view, the rules of its functioning were described using examples from English and Slavic languages; the author offers a two-level classification of functions: the functions were divided into two main blocks – searching and creative ones, within each group more specific sub-functions were singled out within. We used a continuous sampling method for selecting hashtags. As a result, we researched more than 5000 hashtags extracted from posts of users living in 13 countries and writing in Russian, Belarusian, Ukrainian, Polish, Czech, English and other languages. For more detailed analysis of the research object, we used a descriptive method using the techniques of generalization, interpretation and classification, the method of linguistic comparison, contextual analysis, elements of semantic component analysis. It was concluded that some changes occurred in the priorities of the hashtag functions from primary searching function, which helps text space organization, to the creative one, which influences the author’s personality disclosure and audience-author interaction and is associated with an increasing attention to the personal brand and the personality of the author.
40
Gupta, Vibhuti, and Rattikorn Hewett. "Real-Time Tweet Analytics Using Hybrid Hashtags on Twitter Big Data Streams." Information 11, no. 7 (June 30, 2020): 341. http://dx.doi.org/10.3390/info11070341.
Full textAbstract:
Twitter is a microblogging platform that generates large volumes of data with high velocity. This daily generation of unbounded and continuous data leads to Big Data streams that often require real-time distributed and fully automated processing. Hashtags, hyperlinked words in tweets, are widely used for tweet topic classification, retrieval, and clustering. Hashtags are used widely for analyzing tweet sentiments where emotions can be classified without contexts. However, regardless of the wide usage of hashtags, general tweet topic classification using hashtags is challenging due to its evolving nature, lack of context, slang, abbreviations, and non-standardized expression by users. Most existing approaches, which utilize hashtags for tweet topic classification, focus on extracting hashtag concepts from external lexicon resources to derive semantics. However, due to the rapid evolution and non-standardized expression of hashtags, the majority of these lexicon resources either suffer from the lack of hashtag words in their knowledge bases or use multiple resources at once to derive semantics, which make them unscalable. Along with scalable and automated techniques for tweet topic classification using hashtags, there is also a requirement for real-time analytics approaches to handle huge and dynamic flows of textual streams generated by Twitter. To address these problems, this paper first presents a novel semi-automated technique that derives semantically relevant hashtags using a domain-specific knowledge base of topic concepts and combines them with the existing tweet-based-hashtags to produce Hybrid Hashtags. Further, to deal with the speed and volume of Big Data streams of tweets, we present an online approach that updates the preprocessing and learning model incrementally in a real-time streaming environment using the distributed framework, Apache Storm. Finally, to fully exploit the batch and stream environment performance advantages, we propose a comprehensive framework (Hybrid Hashtag-based Tweet topic classification (HHTC) framework) that combines batch and online mechanisms in the most effective way. Extensive experimental evaluations on a large volume of Twitter data show that the batch and online mechanisms, along with their combination in the proposed framework, are scalable, efficient, and provide effective tweet topic classification using hashtags.
41
Pratiwi, Andi Misbahul. "Mengupayakan Keadilan Bagi Korban Kekerasan Seksual Melalui Aktivisme Tagar: Kesempatan dan Kerentanan di Indonesia." Jurnal Perempuan 26, no. 3 (December 11, 2021): 207–18. http://dx.doi.org/10.34309/jp.v26i3.617.
Full textAbstract:
Digital technology brings new opportunities to accessing justice for women and marginalized groups after being excluded from conventional-masculine technology for decades. In the internet era, the use of social media has become very massive and intensive, therefore feminist activism in this digital space is unavoidable. Hashtag activism has become popular since the #MeToo movement and such an opportunity to seek justice for victims and survivors through voicing and documenting their voices. The use of hashtags (#) opens up opportunities for victims’ stories to be documented, connect with other stories, and go viral. In Indonesia, the use of hashtags in activism also occurs in more local contexts such as #KitaAgni, #SaveIbuNuril, #UIITidakAman, #KamiBersamaKorban, and #SahkanRUUPKS. Some hashtag activism has succeeded in initiating follow-up actions in the offline world, although not always viral stories get satisfactory case resolutions. This study uses a qualitative approach, and collecting the data through literature studies, especially on feminist theories ariund technology and digital such as; Science and Technology Studies (STS) feminism, cyberfeminism, technofeminism, and feminist digital activism. This paper finds that the digital space is a contested space where there are opportunities and vulnerabilities for victims, activists, and netizens to seek justice through hashtag activism.
42
Sebastian, Melinda. "Instagram and Gendered Surveillance: Ways of Seeing the Hashtag." Surveillance & Society 17, no. 1/2 (March 31, 2019): 40–45. http://dx.doi.org/10.24908/ss.v17i1/2.12938.
Full textAbstract:
This research examines gendered surveillance on Instagram. The hashtag serves as an affordance across platforms, and this work expands on the literature of the rhetorical functions of hashtags. Rather than focusing on the hashtag itself as the problem, I instead use it as a lens to examine an extant social issue that is beginning to receive attention from the growing body of feminist surveillance research. When Instagram allows certain terms and hashtags to flourish for weeks, months, and even years without removal, this type of rhetoric and image combination functions to socially isolate a particular group in a heteronormative and nonconsensual way that reproduces existing inequalities. Instagram (and also Facebook who owns it) has the opportunity to promote whatever content it chooses and to put forth whatever narrative or rhetorical formation of the world it wants to see. What world does Instagram want?
43
Laestadius, Linnea I., Kendall Penndorf, Melissa Seidl, Pallav Pokhrel, Ryan Patrick, and Young Ik Cho. "Young Adult Identification and Perception of Hashtag-Based Vaping Claims on Instagram." Health Education & Behavior 47, no. 4 (June 8, 2020): 611–18. http://dx.doi.org/10.1177/1090198120928992.
Full textAbstract:
Social media platforms are home to large volumes of ambiguous hashtag-based claims about the health, modified-risk, and cessation benefits of electronic cigarette products (e.g., #Vapingsavedmylife). The objective of this study was to qualitatively explore how young adults interpret these hashtags on the popular platform Instagram. Specifically, we sought to identify if they view these hashtags as making health-related claims, and if they find these claims to be credible and valid. We conducted 12 focus groups in 2018 with non–tobacco users, smokers, dual users, and vapers between the ages of 18 and 24 ( n = 69). Using real Instagram posts to guide discussion, participants reflected on the meaning of potentially claims-making hashtags. Participants interpreted the majority of the hashtags as making health-related claims. However, many participants felt that the claims were too exaggerated to be entirely valid. Some participants, including dual users and vapers, argued that smoking and vaping were largely equivalent. Smokers were particularly skeptical of claims. Findings suggest that the U. S. Food and Drug Administration should consider hashtag-based claims in their regulatory efforts. However, further research is needed on how to pragmatically address claims taking the form of hashtags given legal and practical constraints.
44
Eddington, Sean M. "The Communicative Constitution of Hate Organizations Online: A Semantic Network Analysis of “Make America Great Again”." Social Media + Society 4, no. 3 (July 2018): 205630511879076. http://dx.doi.org/10.1177/2056305118790763.
Full textAbstract:
In the context of the 2016 U.S. Presidential Election, President Donald Trump’s use of Twitter to connect with followers and supporters created unprecedented access to Trump’s online political campaign. In using the campaign slogan, “Make America Great Again” (or its acronym “MAGA”), Trump communicatively organized and controlled media systems by offering his followers an opportunity to connect with his campaign through the discursive hashtag. In effect, the strategic use of these networks over time communicatively constituted an effective and winning political organization; however, Trump’s political organization was not without connections to far-right and hate groups that coalesced in and around the hashtag. Semantic network analyses uncovered how the textual nature of #MAGA organized connections between hashtags, and, in doing so, exposed connections to overtly White supremacist groups within the United States and the United Kingdom throughout late November 2016. Cluster analyses further uncovered semantic connections to White supremacist and White nationalist groups throughout the hashtag networks connected to the central slogan of Trump’s presidential campaign. Theoretically, these findings contribute to the ways in which hashtag networks show how Trump’s support developed and united around particular organizing processes and White nationalist language, and provide insights into how these networks discursively create and connect White supremacists’ organizations to Trump’s campaign.
45
Dahiya, Saurabh, Ankit J. Kansagra, and Syed S. Ali. "Increasing Use of Social Media at Annual ASH Meetings." Blood 126, no. 23 (December 3, 2015): 4469. http://dx.doi.org/10.1182/blood.v126.23.4469.4469.
Full textAbstract:
Abstract Background: The use of social media is expanding in medicine. More and more healthcare professionals, patients and advocates are using social media as a common platform to enhance communication. Methods: Each year American Society of Hematology (ASH) creates a hashtag (#) followed by year of the annual meeting (e.g. ASH 2014 had this hashtag: #ASH14) on Twitter. We conducted a retrospective study of annual meeting's hashtag use on Twitter for past 4 annual meetings using data from Symplur, LLC. Symplur is an online forum offering analytics of the global Twitter based conversations. Following hashtags were used for analysis, #ASH11, #ASH12, #ASH13 and #ASH14. Results: Overall there is an increasing trend for use of annual meeting's hashtag (see table 1). Last year's meeting generated over 72 million impressions. Number of tweets being sent out is doubling every year. More twitter users are engaging in conversations than the year before using annual meeting's hashtag. Last year almost 4000 individual twitter accounts were used during the annual meeting. Number of tweets per participant has stayed relatively constant over past four years. @ash_hematology remains the most commonly mentioned twitter handle every year since 2011. In 2014 itself, @ash_hematology was mentioned over 2000 times. Conclusion: Twitter is a very powerful tool that amplifies the content of scientific meetings. Use of twitter using meeting's hashtag is increasing every year at annual ASH meetings. This analysis provides a snapshot of twitter activity at the conference. Avenues for further research are: trend identification, "influencer" identification, and qualitative analysis. Interdisciplinary research should focus on evaluation methods that can assess the quality, value, and impact of tweeting. Table 1. Year Impressions Tweets Participants Average tweet per participant 2011 12,255,646 3123 606 5 2012 18,153,786 5,094 870 6 2013 30,018,580 12,233 1942 6 2014 72,433,270 24,185 3977 6 Disclosures No relevant conflicts of interest to declare.
46
Zhang, Suwei, Yuan Yao, Feng Xu, Hanghang Tong, Xiaohui Yan, and Jian Lu. "Hashtag Recommendation for Photo Sharing Services." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5805–12. http://dx.doi.org/10.1609/aaai.v33i01.33015805.
Full textAbstract:
Hashtags can greatly facilitate content navigation and improve user engagement in social media. Meaningful as it might be, recommending hashtags for photo sharing services such as Instagram and Pinterest remains a daunting task due to the following two reasons. On the endogenous side, posts in photo sharing services often contain both images and text, which are likely to be correlated with each other. Therefore, it is crucial to coherently model both image and text as well as the interaction between them. On the exogenous side, hashtags are generated by users and different users might come up with different tags for similar posts, due to their different preference and/or community effect. Therefore, it is highly desirable to characterize the users’ tagging habits. In this paper, we propose an integral and effective hashtag recommendation approach for photo sharing services. In particular, the proposed approach considers both the endogenous and exogenous effects by a content modeling module and a habit modeling module, respectively. For the content modeling module, we adopt the parallel co-attention mechanism to coherently model both image and text as well as the interaction between them; for the habit modeling module, we introduce an external memory unit to characterize the historical tagging habit of each user. The overall hashtag recommendations are generated on the basis of both the post features from the content modeling module and the habit influences from the habit modeling module. We evaluate the proposed approach on real Instagram data. The experimental results demonstrate that the proposed approach significantly outperforms the state-of-theart methods in terms of recommendation accuracy, and that both content modeling and habit modeling contribute significantly to the overall recommendation accuracy.
47
Fabricius, Anne H. "#aintnobodygottimeforthat: cultural appropriation, stylization and the social life of hashtag interjectionality." Scandinavian Studies in Language 10, no. 1 (May 31, 2019): 85–97. http://dx.doi.org/10.7146/sss.v10i1.114672.
Full textAbstract:
Th is paper will discuss a particular hashtag meme as one example of a potential new manifestation of interjectionality, engendered and fostered in the written online context of social media. Th e case derives from a video meme and hashtag from the United States which ‘went viral’ in 2012. We will ask to what extent hashtags might perform interjectional-type functions over and above their referential functions, thereby having links to other, more prototypically interjectional elements. Th e case will also be discussed from multiple sociolinguistic perspectives: as an example of the (indirect) signifying of ‘whiteness’ through ‘black’ discourse, as cultural appropriation in the context of potential policing of these racial divides in the United States, and as a case of performative stylization which highlights grammatical markers while simultaneously downplaying phonological markers of African American English. We will end by speculating as to the implications of the rise of (variant forms of) hashtags for processes of creative language use in the future.
48
Leite, Dario, and Cláudio Novaes Pinto Coelho. "A influência da hashtag nas interações das redes sociais da internet." Revista de Estudos Universitários - REU 46, no. 2 (December 17, 2020): 279–305. http://dx.doi.org/10.22484/2177-5788.2020v46n2p279-305.
Full textAbstract:
O uso da rede social Twitter, em segunda tela, permite a milhares de torcedores se manifestarem durante as transmissões ao vivo de futebol pela televisão. Dentro desse fenômeno, observado a partir do conceito de sociedade do espetáculo, de Guy Debord, o presente artigo investigou a influência do uso das hashtags. Foi feita uma análise de rede social em seis jogos de futebol. Percebemos que a hashtag, mais do que um mero indexador de assuntos, pode se colocar como um actante – dentro da conceituação formulada pela Teoria do Ator-rede, de Bruno Latour – tendo um papel determinante na interação produzida. A percepção desse papel da hashtag vai contribuir para o entendimento do agir dentro das redes sociais da internet.
49
Tovo, Anna, Samuele Stivanello, Amos Maritan, Samir Suweis, Stefano Favaro, and Marco Formentin. "Upscaling human activity data: A statistical ecology approach." PLOS ONE 16, no. 7 (July 1, 2021): e0253461. http://dx.doi.org/10.1371/journal.pone.0253461.
Full textAbstract:
Big data require new techniques to handle the information they come with. Here we consider four datasets (email communication, Twitter posts, Wikipedia articles and Gutenberg books) and propose a novel statistical framework to predict global statistics from random samples. More precisely, we infer the number of senders, hashtags and words of the whole dataset and how their abundances (i.e. the popularity of a hashtag) change through scales from a small sample of sent emails per sender, posts per hashtag and word occurrences. Our approach is grounded on statistical ecology as we map inference of human activities into the unseen species problem in biodiversity. Our findings may have applications to resource management in emails, collective attention monitoring in Twitter and language learning process in word databases.
50
Mehmood, Raja Majid, Guo Xinyi, Liu Cuiting, and Wang Ruisi. "3D Based Visualization Tool to Analyze the Influential Topics via Hashtags on Instagram Platform." Academic Research Community publication 4, no. 2 (December 30, 2020): 26. http://dx.doi.org/10.21625/archive.v4i2.753.
Full textAbstract:
This paper intends to develop an interactive, comprehensive information visualization platform of Instagram hashtag analysis. Instagram hashtags has developed themselves into all different kinds of group or communities for users to share hobbies and find similar friends. In order to analyze topic influence and user interest trend from Instagram, which contains billions of end-users and has worldwide influence, hashtag analysis is necessary to gather such information and compare the proportion of people involving in each tags and rank them to visualize. The visualization is developed in 3D space and consists of time-varying data flow of tags, together with tag comparison analysis, as well as event researches. In the rest of the paper, we mainly discuss the design idea and the development process of the system. An example of the system design work will be shown in the discussion, which involves 4 popular hashtags discussed on Instagram and are shown on the system, displayed as an 3D histogram, together with another comparison histogram to compare different tags, as well as an event view in the back.