Zobrazeno 1 - 10
of 6 220
pro vyhledávání: '"Twitter/X"'
Approximately 50% of tweets in X's user timelines are personalized recommendations from accounts they do not follow. This raises a critical question: what political content are users exposed to beyond their established networks, and how might this in
Externí odkaz:
http://arxiv.org/abs/2411.01852
Autor:
Balasubramanian, Ashwin, Zou, Vito, Narayana, Hitesh, You, Christina, Luceri, Luca, Ferrara, Emilio
In this paper, we introduce the first release of a large-scale dataset capturing discourse on $\mathbb{X}$ (a.k.a., Twitter) related to the upcoming 2024 U.S. Presidential Election. Our dataset comprises 22 million publicly available posts on X.com,
Externí odkaz:
http://arxiv.org/abs/2411.00376
The aspect-based sentiment analysis (ABSA) is a standard NLP task with numerous approaches and benchmarks, where large language models (LLM) represent the current state-of-the-art. We focus on ABSA subtasks based on Twitter/X data in underrepresented
Externí odkaz:
http://arxiv.org/abs/2408.02044
Social media personalization algorithms increasingly influence the flow of civic information through society, resulting in concerns about "filter bubbles", "echo chambers", and other ways they might exacerbate ideological segregation and fan the spre
Externí odkaz:
http://arxiv.org/abs/2406.17097
Autor:
Peters, Uwe, Quintana, Ignacio Ojea
Generics (unquantified generalizations) are thought to be pervasive in communication and when they are about social groups, this may offend and polarize people because generics gloss over variations between individuals. Generics about social groups m
Externí odkaz:
http://arxiv.org/abs/2405.08331
Autor:
TÜYLÜOĞLU, Esra1 dresratuyluoglu@gmail.com
Publikováno v:
Journal of Business Research-Turk / Isletme Arastirmalari Dergisi. 2023, Vol. 15 Issue 4, p2863-2879. 17p.
Autor:
Khaq, Ilnafi Sabilal1 ilnafikhaq@gmail.com, Wulandari, Lia1 lia.wulandari@upnvj.ac.id
Publikováno v:
Jurnal Wacana Politik. Jan2024, Vol. 9 Issue 1, p1-10. 10p.
Autor:
Yang, Wen
This study investigates echo chambers in social networks through an analysis of Twitter news accounts. Utilizing bias labels from the AllSides website, we construct a dataset representing six dimensions of news bias. Through manual extraction of foll
Externí odkaz:
http://arxiv.org/abs/2404.15631
Autor:
Ng, Qin Xiang1,2,3 (AUTHOR) ng.qin.xiang@u.nus.edu, Lim, Yu Liang4 (AUTHOR), Xin, Xiaohui2 (AUTHOR), Ong, Clarence1 (AUTHOR), Ng, Wee Khoon4 (AUTHOR), Thumboo, Julian2,5 (AUTHOR), Tan, Hiang Khoon3,6,7 (AUTHOR)
Publikováno v:
BMC Public Health. 7/16/2024, Vol. 24 Issue 1, p1-8. 8p.
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