Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines
Tóm tắt
Từ khóa
Tài liệu tham khảo
Abramowitz, A., & McCoy, J. (2019). United states: Racial resentment, negative partisanship, and polarization in trump’s America. The Annals of the American Academy of Political and Social Science, 681(1), 137–156.
Alorainy, W., Burnap, P., Liu, H., & Williams, M. L. (2019). The enemy among us: Detecting cyber hate speech with threats-based othering language embeddings. ACM Transactions on the Web (TWEB), 13(3), 1–26.
Antoci, A., Delfino, A., Paglieri, F., Panebianco, F., & Sabatini, F. (2016). Civility vs. incivility in online social interactions: An evolutionary approach. PloS One, 11(11), e0164286.
Arif, A., Stewart, L. G., & Starbird, K. (2018). Acting the part: Examining information operations within #BlackLivesMatter discourse. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1–27.
Awan, I., & Zempi, I. (2016). The affinity between online and offline anti-muslim hate crime: Dynamics and impacts. Aggression and Violent Behavior, 27, 1–8.
Badawy, A., Ferrara, E., & Lerman, K. (2018). Analyzing the digital traces of political manipulation: The 2016 Russian interference Twitter campaign. In 2018 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM) (pp. 258–265). IEEE.
Badjatiya, P., Gupta, S., Gupta, M., & Varma, V. (2017). Deep learning for hate speech detection in tweets. In Proceedings of the 26th international conference on World Wide Web companion (pp. 759–760).
Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. F., et al. (2018). Exposure to opposing views on social media can increase political polarization. Proceedings of the National Academy of Sciences, 115(37), 9216–9221.
Bail, C. A., Guay, B., Maloney, E., Combs, A., Hillygus, D. S., Merhout, F., et al. (2020). Assessing the Russian Internet Research Agency’s impact on the political attitudes and behaviors of American Twitter users in late 2017. Proceedings of the National Academy of Sciences, 117(1), 243–250.
Bennett, W. L., & Livingston, S. (2018). The disinformation order: Disruptive communication and the decline of democratic institutions. European Journal of Communication, 33(2), 122–139.
Beskow, D. M. (2020). Finding and characterizing information warfare campaigns. Ph.D. thesis, Carnegie Mellon University.
Beskow, D. M., & Carley, K. M. (2018). Bot conversations are different: Leveraging network metrics for bot detection in Twitter. In 2018 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM) (pp. 825–832). IEEE.
Beskow, D. M., & Carley, K. M. (2019). Agent based simulation of bot disinformation maneuvers in Twitter. In: 2019 Winter simulation conference (WSC) (pp. 750–761). IEEE.
Beskow, D. M., & Carley, K. M. (2020). Characterization and comparison of Russian and Chinese disinformation campaigns. In Disinformation, misinformation, and fake news in social media (pp. 63–81). Springer.
Beskow, D., Carley, K. M.: Social cybersecurity. Springer (forthcoming).
Beskow, D. M., & Carley, K. M. (2019). Social cybersecurity: An emerging national security requirement. Military Review, 99(2), 117.
Bilewicz, M., & Soral, W. (2020). Hate speech epidemic. The dynamic effects of derogatory language on intergroup relations and political radicalization. Political Psychology, 41, 3–33.
Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, É. (2011). The Louvain method for community detection in large networks. Journal of Statistical Mechanics: Theory and Experiment, 10, P10008.
Borgatti, S. P., Carley, K. M., & Krackhardt, D. (2006). On the robustness of centrality measures under conditions of imperfect data. Social Networks, 28(2), 124–136.
Bradshaw, S., & Howard, P. N. (2018). The global organization of social media disinformation campaigns. Journal of International Affairs, 71(1.5), 23–32.
Calvert, C. (1997). Hate speech and its harms: A communication theory perspective. Journal of Communication, 47(1), 4–19.
Carley, K. M., Cervone, G., Agarwal, N., & Liu, H. (2018). Social cyber-security. In International conference on social computing, behavioral-cultural modeling and prediction and behavior representation in modeling and simulation (pp. 389–394). Springer.
Carley, L.R., Reminga, J., & Carley, K.M. (2018). Ora & netmapper. In: International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. Springer
Chen, E., Lerman, K., & Ferrara, E. (2020). COVID-19: The first public coronavirus Twitter dataset. arXiv preprint arXiv:2003.07372.
Chetty, N., & Alathur, S. (2018). Hate speech review in the context of online social networks. Aggression and Violent Behavior, 40, 108–118.
Chiriboga, D., Garay, J., Buss, P., Madrigal, R. S., & Rispel, L. C. (2020). Health inequity during the COVID-19 pandemic: A cry for ethical global leadership. The Lancet, 395(10238), 1690–1691.
Chu, Z., Gianvecchio, S., Wang, H., & Jajodia, S. (2012). Detecting automation of twitter accounts: Are you a human, bot, or cyborg? IEEE Transactions on Dependable and Secure Computing, 9(6), 811–824.
Crenshaw, K. (1990). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43, 1241.
Cresci, S., Lillo, F., Regoli, D., Tardelli, S., & Tesconi, M. (2019). Cashtag piggybacking: Uncovering spam and bot activity in stock microblogs on twitter. ACM Transactions on the Web (TWEB), 13(2), 1–27.
Davidson, T., Warmsley, D., Macy, M., & Weber, I. (2017). Automated hate speech detection and the problem of offensive language. In Eleventh international AAAI conference on web and social media
Devakumar, D., Shannon, G., Bhopal, S. S., & Abubakar, I. (2020). Racism and discrimination in COVID-19 responses. The Lancet, 395(10231), 1194.
ElSherief, M., Kulkarni, V., Nguyen, D., Wang, W. Y., & Belding, E. (2018). Hate lingo: A target-based linguistic analysis of hate speech in social media. In Twelfth international AAAI conference on web and social media
ElSherief, M., Nilizadeh, S., Nguyen, D., Vigna, G., & Belding, E. (2018). Peer to peer hate: Hate speech instigators and their targets. In: Twelfth international aaai conference on web and social media
Ferrara, E., Varol, O., Davis, C., Menczer, F., & Flammini, A. (2016). The rise of social bots. Communications of the ACM, 59(7), 96–104.
Fortuna, P., & Nunes, S. (2018). A survey on automatic detection of hate speech in text. ACM Computing Surveys (CSUR), 51(4), 1–30.
Gallotti, R., Valle, F., Castaldo, N., Sacco, P., & De Domenico, M. (2020). Assessing the risks of“ infodemics” in response to covid-19 epidemics. arXiv preprint arXiv:2004.03997.
Garimella, K., De Francisci Morales, G., Gionis, A., & Mathioudakis, M. (2018). Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship. In: Proceedings of the 2018 World Wide Web Conference (pp. 913–922).
Geiger, R. S. (2016). Bot-based collective blocklists in Twitter: The counterpublic moderation of harassment in a networked public space. Information, Communication and Society, 19(6), 787–803.
Gosling, S. D., Sandy, C. J., John, O. P., & Potter, J. (2010). Wired but not weird: The promise of the internet in reaching more diverse samples. Behavioral and Brain Sciences, 33(2–3), 94.
Gunturi, V. M., Shekhar, S., Joseph, K., & Carley, K. M. (2017). Scalable computational techniques for centrality metrics on temporally detailed social network. Machine Learning, 106(8), 1133–1169.
Henrich, J., Heine, S. J., & Norenzayan, A. (2010). Most people are not WEIRD. Nature, 466(7302), 29.
Horton, R. (2020). Offline: COVID-19—What we can expect to come. Lancet (London, England), 395(10240), 1821.
Innes, M. (2020). Techniques of disinformation: Constructing and communicating “soft facts” after terrorism. The British Journal of Sociology, 71(2), 284–299. https://doi.org/10.1111/1468-4446.12735._eprint.
Johnson, N. F., Leahy, R., Restrepo, N. J., Velasquez, N., Zheng, M., Manrique, P., et al. (2019). Hidden resilience and adaptive dynamics of the global online hate ecology. Nature, 573(7773), 261–265. https://doi.org/10.1038/s41586-019-1494-7.
Joseph, K., Wei, W., Benigni, M., & Carley, K. M. (2016). A social-event based approach to sentiment analysis of identities and behaviors in text. The Journal of Mathematical Sociology, 40(3), 137–166.
Kennedy, B., Jin, X., Davani, A. M., Dehghani, M., & Ren, X. (2020). Contextualizing hate speech classifiers with post-hoc explanation. arXiv preprint arXiv:2005.02439.
Kim, B. (2020). Effects of Social Grooming on Incivility in COVID-19. Cyberpsychology, Behavior, and Social Networking.,. https://doi.org/10.1089/cyber.2020.0201.
Krackhardt, D., & Stern, R.N. (1988). Informal networks and organizational crises: An experimental simulation. In Social Psychology Quarterly, 123–140
Lazer, D., Pentland, A. S., Adamic, L., Aral, S., Barabasi, A. L., Brewer, D., et al. (2009). Life in the network: The coming age of computational social science. Science (New York, NY), 323(5915), 721.
Leader, T., Mullen, B., & Rice, D. (2009). Complexity and valence in ethnophaulisms and exclusion of ethnic out-groups: What puts the“ hate” into hate speech? Journal of Personality and Social Psychology, 96(1), 170.
Li, Y., & Galea, S. (2020). Racism and the COVID-19 epidemic: Recommendations for health care workers. American Journal of Public Health, 110(7), 956–957.
Luengo-Oroz, M., Hoffmann Pham, K., Bullock, J., Kirkpatrick, R., Luccioni, A., Rubel, S., et al. (2020). Artificial intelligence cooperation to support the global response to COVID-19. Nature Machine Intelligence, 2(6), 295–297. https://doi.org/10.1038/s42256-020-0184-3.
MacAvaney, S., Yao, H. R., Yang, E., Russell, K., Goharian, N., & Frieder, O. (2019). Hate speech detection: Challenges and solutions. PloS One, 14(8), e0221152.
Martinez-Juarez, L.A., Sedas, A.C., Orcutt, M., & Bhopal, R. (2020). Governments and international institutions should urgently attend to the unjust disparities that COVID-19 is exposing and causing. EClinicalMedicine
Mathew, B., Saha, P., Tharad, H., Rajgaria, S., Singhania, P., Maity, S. K., et al. (2019). Thou shalt not hate: Countering online hate speech. Proceedings of the International AAAI Conference on Web and Social Media, 13, 369–380.
Mohar, B. (1989). Isoperimetric numbers of graphs. Journal of Combinatorial Theory, Series B, 47(3), 274–291.
Mønsted, B., Sapieżyński, P., Ferrara, E., & Lehmann, S. (2017). Evidence of complex contagion of information in social media: An experiment using Twitter bots. PloS One, 12(9), e0184148.
Montiel, C. J., Boller, A. J., Uyheng, J., & Espina, E. A. (2019). Narrative congruence between populist president Duterte and the Filipino public: Shifting global alliances from the United States to China. Journal of Community and Applied Social Psychology, 29(6), 520–534.
Morgan, S. (2018). Fake news, disinformation, manipulation and online tactics to undermine democracy. Journal of Cyber Policy, 3(1), 39–43.
Morstatter, F., Pfeffer, J., Liu, H., & Carley, K. M. (2013). Is the sample good enough? comparing data from Twitter’s streaming API with Twitter’s firehose. In Seventh international AAAI conference on web and social media.
Ong, J. C., & Cabañes, J. V. A. (2018). Architects of networked disinformation: Behind the scenes of troll accounts and fake news production in the Philippines. Architects of networked disinformation: Behind the scenes of troll accounts and fake news production in the Philippines.
Ong, J. C., Tapsell, R., & Curato, N. (2019). Tracking digital disinformation in the 2019 Philippine midterm election. New Mandala.
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003). Psychological aspects of natural language use: Our words, our selves. Annual Review of Psychology, 54(1), 547–577.
Pohjonen, M., & Udupa, S. (2017). Extreme speech online: An anthropological critique of hate speech debates. International Journal of Communication, 11, 19.
Priante, A., Hiemstra, D., Van Den Broek, T., Saeed, A., Ehrenhard, M., & Need, A. (2016). # whoami in 160 characters? classifying social identities based on twitter profile descriptions. In: Proceedings of the first workshop on NLP and computational social science (pp. 55–65).
Reicher, S., & Stott, C. (2020). On order and disorder during the COVID-19 pandemic. British Journal of Social Psychology, 59(3), 694–702.
Roussos, G., & Dovidio, J. F. (2018). Hate speech is in the eye of the beholder: The influence of racial attitudes and freedom of speech beliefs on perceptions of racially motivated threats of violence. Social Psychological and Personality Science, 9(2), 176–185.
Rutledge, P. E. (2020). Trump, covid-19, and the war on expertise. The American Review of Public Administration, 50(6–7), 505–511.
Shao, C., Ciampaglia, G. L., Varol, O., Yang, K. C., Flammini, A., & Menczer, F. (2018). The spread of low-credibility content by social bots. Nature Communications, 9(1), 1–9.
Soral, W., Bilewicz, M., & Winiewski, M. (2018). Exposure to hate speech increases prejudice through desensitization. Aggressive Behavior, 44(2), 136–146.
Starbird, K. (2019). Disinformation’s spread: Bots, trolls and all of us. Nature, 571(7766), 449–450.
Starbird, K., Arif, A., & Wilson, T. (2019). Disinformation as collaborative work: Surfacing the participatory nature of strategic information operations. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1–26.
Stechemesser, A., Wenz, L., & Levermann, A. (2020). Corona crisis fuels racially profiled hate in social media networks. EClinicalMedicine,. https://doi.org/10.1016/j.eclinm.2020.100372.
Stella, M., Ferrara, E., & De Domenico, M. (2018). Bots increase exposure to negative and inflammatory content in online social systems. Proceedings of the National Academy of Sciences, 115(49), 12435–12440.
Stewart, L. G., Arif, A., Nied, A. C., Spiro, E. S., & Starbird, K. (2017). Drawing the lines of contention: Networked frame contests within #BlackLivesMatter discourse. Proceedings of the ACM on Human-Computer Interaction, 1(CSCW), 1–23.
Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29(1), 24–54.
Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: Guaranteeing well-connected communities. Scientific Reports, 9(1), 1–12.
Uyheng, J., & Carley, K. M. (2019). Characterizing bot networks on Twitter: An empirical analysis of contentious issues in the Asia-Pacific. In International conference on social computing (pp. 153–162). Behavioral-cultural modeling and prediction and behavior representation in modeling and simulation Washington DC, USA: Springer.
Uyheng, J., & Carley, K.M. (2020). Bot impacts on public sentiment and community structures: Comparative analysis of three elections in the Asia-Pacific. In International conference on social computing, behavioral-cultural modeling and prediction and behavior representation in modeling and simulation. Springer, Washington DC, USA.
Uyheng, J., & Montiel, C.J. Populist polarization in postcolonial Philippines: Sociolinguistic rifts in online drug war discourse. European Journal of Social Psychology (in press). https://doi.org/10.1002/ejsp.2716.
Uyheng, J., Magelinski, T., Villa-Cox, R., Sowa, C., & Carley, K. M. (2019). Interoperable pipelines for social cyber-security: Assessing Twitter information operations during NATO Trident Juncture 2018. Computational and Mathematical Organization Theory, 1–19.
Van Bavel, J.J., Baicker, K., Boggio, P.S., Capraro, V., Cichocka, A., Cikara, M., Crockett, M. J., Crum, A.J., Douglas, K. M., & Druckman, J. N., et al. (2020). Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour, 1–12.
Varol, O., Ferrara, E., Davis, C. A., Menczer, F., & Flammini, A. (2017). Online human-bot interactions: Detection, estimation, and characterization. In: Eleventh international AAAI conference on web and social media.
Waqas, A., Salminen, J., Jung, Sg, Almerekhi, H., & Jansen, B. J. (2019). Mapping online hate: A scientometric analysis on research trends and hotspots in research on online hate. PloS One, 14(9), e0222194.
Warner, W., & Hirschberg, J. (2012). Detecting hate speech on the world wide web. In Proceedings of the second workshop on language in social media (pp. 19–26).
Williams, M. L., Burnap, P., Javed, A., Liu, H., & Ozalp, S. (2020). Hate in the machine: Anti-Black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. The British Journal of Criminology, 60(1), 93–117.
World Health Organization: Coronavirus disease (COVID-19) weekly epidemiological update. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200914-weekly-epi-update-5.pdf (2020).
Ziems, C., He, B., Soni, S., & Kumar, S. (2020). Racism is a virus: Anti-asian hate and counterhate in social media during the covid-19 crisis. arXiv preprint arXiv:2005.12423.