The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Spread of Hate Speech in Online Social Media
Open accessAbstract
Hate speech is considered to be one of the major issues currently plaguing the online social media. With online hate speech culminating in gruesome scenarios like the Rohingya genocide in Myanmar, anti-Muslim mob violence in Sri Lanka, and the Pittsburgh synagogue shooting, there is a dire need to understand the dynamics of user interaction that facilitate the spread of such hateful content. In this paper, we perform the first study that looks into the diffusion dynamics of the posts made by hateful and non-hateful users on Gab (Gab.com). We collect a massive dataset of 341K users with 21M posts and investigate the diffusion of the posts generated by hateful and non-hateful users. We observe that the content generated by the hateful users tend to spread faster, farther and reach a much wider audience as compared to the content generated by normal users. We further analyze the hateful and non-hateful users on the basis of their account and network characteristics. An important finding is that the hateful users are far more densely connected among themselves. Overall, our study provides the first cross-sectional view of how hateful users diffuse hate content in online social media.
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Citations
Cites
The spread of true and false news online
Vosoughi, S., Roy, D., & Aral, S. (2018) · Science · doi:10.1126/science.aap9559 · Cited by 8,847 · cited 2×
“However, there are several works that looks into diffusion in fake news (Vosoughi, Roy, and They observe that content virality is the main driver for recurrence.”
BackgroundMethodAutomated Hate Speech Detection and the Problem of Offensive Language
Davidson, T., Warmsley, D., Macy, M., & Weber, I. (2017) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v11i1.14955 · Cited by 2,610
The spreading of misinformation online
Del Vicario, M., Bessi, A., Zollo, F., Petroni, F., Scala, A., Caldarelli, G., Stanley, H. E., & Quattrociocchi, W. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1517441113 · Cited by 2,407
Everyone's an influencer: quantifying influence on twitter
Bakshy, E., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011) · Proceedings of the fourth ACM international conference on Web search and data mining · doi:10.1145/1935826.1935845 · Cited by 1,689
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
Waseem, Z., & Hovy, D. (2016) · Proceedings of the NAACL Student Research Workshop · doi:10.18653/v1/n16-2013 · Cited by 1,655
Abusive Language Detection in Online User Content
Nobata, C., Tetreault, J., Thomas, A., Mehdad, Y., & Chang, Y. (2016) · Proceedings of the 25th International Conference on World Wide Web · doi:10.1145/2872427.2883062 · Cited by 1,122
Naïve Learning in Social Networks and the Wisdom of Crowds
Golub, B., & Jackson, M. O. (2010) · American Economic Journal: Microeconomics · doi:10.1257/mic.2.1.112 · Cited by 979
Deep Learning for Hate Speech Detection in Tweets
Badjatiya, P., Gupta, S., Gupta, M., & Varma, V. (2017) · Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion · doi:10.1145/3041021.3054223 · Cited by 849
Cheng, J., Adamic, L. A., Dow, P. A., Kleinberg, J. M., & Leskovec, J. (2014) · Cited by 787
Hate Speech Detection with Comment Embeddings
Djuric, N., Zhou, J., Morris, R., Grbovic, M., Radosavljevic, V., & Bhamidipati, N. (2015) · Proceedings of the 24th International Conference on World Wide Web · doi:10.1145/2740908.2742760 · Cited by 712
Cited by
HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection
Mathew, B., Saha, P., Yimam, S. M., Biemann, C., Goyal, P., & Mukherjee, A. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i17.17745 · Cited by 513
Self-citationSocial Media, Echo Chambers, and Political Polarization
Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373
Misinformation, Disinformation, and Online Propaganda
Guess, A. M., & Lyons, B. A. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.003 · Cited by 284
Understanding the Effect of Deplatforming on Social Networks
Ali, S., Saeed, M. H., Aldreabi, E., Blackburn, J., De Cristofaro, E., Zannettou, S., & Stringhini, G. (2021) · 13th ACM Web Science Conference 2021 · doi:10.1145/3447535.3462637 · Cited by 109
Violent political rhetoric on Twitter
Kim, T. (2023) · Political Science Research and Methods · doi:10.1017/psrm.2022.12 · Cited by 43
Metadata
- Authors
- Mathew, B., Dutt, R., Goyal, P., & Mukherjee, A.
- Venue
- Proceedings of the 10th ACM Conference on Web Science
- Publisher
- ACM
- Published
- 2019-06-26
- Pages
- 173-182
- OpenAlex
- W2903015761
- Cited by
- 348
- References
- 43
- FWCI
- 18.03
- Type
- conference paper
- Language
- en
- Open access
- green
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