Data-driven Understanding of the Disinformation Epidemic

Data-driven Understanding of the Disinformation Epidemic

 

Arguably, one of the greatest inventions of humanity is the Web. Despite the fact it revolutionized our lives, the Web has also introduced or amplified a set of several social issues like the spread of disinformation and hateful content to a large number of people.

In this seminar, we will look into research that focuses on extracting insights from large corpus of data with the goal to understand emerging socio-technical issues on the Web such as the dissemination of disinformation and hateful content. We will read, present, and discuss papers that follow a data-driven approach to analyze large-scale datasets across several axes to study the multi-faceted aspects of emerging issues like disinformation.

During this seminar, the participants will have the opportunity to learn about state-of-the-art techniques and tools that are used for large-scale processing, including, but not limited to, statistical techniques, machine learning, image analysis, and natural language processing techniques.

 

Logistics

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Location: online via Zoom

Lecturers: Yang Zhang

Assistants: Zheng Li (zheng.li@cispa.de), Yugeng Liu (yugeng.liu@cispa.de), Boyang Zhang (boyang.zhang@cispa.de), Xinlei He (xinlei.he@cispa.de)

Time: Every Monday 14:00-15:30, starting from April 25th

 

List of Papers

 

1. Vosoughi, S., Roy, D. and Aral, S., 2018. The spread of true and false news online. Science, 359(6380), pp.1146-1151.
2. Zannettou, S., Caulfield, T., De Cristofaro, E., Kourtellis, N., Leontiadis, I., Sirivianos, M., Stringhini, G. and Blackburn, J., 2017, November. The web centipede: understanding how web communities influence each other through the lens of mainstream and alternative news sources. In Proceedings of the 2017 Internet Measurement Conference (pp. 405-417).
3. Starbird, K., 2017, May. Examining the alternative media ecosystem through the production of alternative narratives of mass shooting events on Twitter. In Eleventh International AAAI Conference on Web and Social Media.
4. Resende, G., Melo, P., Sousa, H., Messias, J., Vasconcelos, M., Almeida, J. and Benevenuto, F., 2019, May. (Mis) Information Dissemination in WhatsApp: Gathering, Analyzing and Countermeasures. In The World Wide Web Conference (pp. 818-828).
5. Zannettou, S., Caulfield, T., Setzer, W., Sirivianos, M., Stringhini, G. and Blackburn, J., 2019, June. Who let the trolls out? towards understanding state-sponsored trolls. In Proceedings of the 10th acm conference on web science (pp. 353-362).
6. Jiang, S., Robertson, R.E. and Wilson, C., 2019, July. Bias misperceived: The role of partisanship and misinformation in youtube comment moderation. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 13, No. 01, pp. 278-289).
7. Kumar, S., West, R. and Leskovec, J., 2016, April. Disinformation on the web: Impact, characteristics, and detection of wikipedia hoaxes. In Proceedings of the 25th international conference on World Wide Web (pp. 591-602).
8. Ribeiro, F.N., Saha, K., Babaei, M., Henrique, L., Messias, J., Benevenuto, F., Goga, O., Gummadi, K.P. and Redmiles, E.M., 2019, January. On microtargeting socially divisive ads: A case study of russia-linked ad campaigns on facebook. In Proceedings of the Conference on Fairness, Accountability, and Transparency (pp. 140-149).
9.  Cha, M., Cha, C., Singh, K., Lima, G., Ahn, Y.Y., Kulshrestha, J. and Varol, O., 2021. Prevalence of misinformation and factchecks on the COVID-19 pandemic in 35 countries: observational infodemiology study. JMIR Human Factors, 8(1), p.e23279
10. Zannettou, S., Caulfield, T., Blackburn, J., De Cristofaro, E., Sirivianos, M., Stringhini, G. and Suarez-Tangil, G., 2018, October. On the origins of memes by means of fringe web communities. In Proceedings of the Internet Measurement Conference 2018 (pp. 188-202).
11. Mathew, B., Dutt, R., Goyal, P. and Mukherjee, A., 2019, June. Spread of hate speech in online social media. In Proceedings of the 10th ACM Conference on Web Science (pp. 173-182).
12. Mariconti, E., Suarez-Tangil, G., Blackburn, J., De Cristofaro, E., Kourtellis, N., Leontiadis, I., Serrano, J.L. and Stringhini, G., 2019. " You Know What to Do" Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), pp.1-21.
13. Zannettou, S., Finkelstein, J., Bradlyn, B. and Blackburn, J., 2020, May. A quantitative approach to understanding online antisemitism. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 786-797).
14. Chandrasekharan, E., Pavalanathan, U., Srinivasan, A., Glynn, A., Eisenstein, J. and Gilbert, E., 2017. You can't stay here: The efficacy of reddit's 2015 ban examined through hate speech. Proceedings of the ACM on Human-Computer Interaction, 1(CSCW), pp.1-22.
15. Ribeiro, M.H., Ottoni, R., West, R., Almeida, V.A. and Meira Jr, W., 2020, January. Auditing radicalization pathways on youtube. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 131-141).
16. Ribeiro, M.H., Jhaver, S., Zannettou, S., Blackburn, J., De Cristofaro, E., Stringhini, G. and West, R., 2020. Does Platform Migration Compromise Content Moderation? Evidence from r/The_Donald and r/Incels. arXiv preprint arXiv:2010.10397.
17. Davidson, T., Warmsley, D., Macy, M. and Weber, I., 2017, May. Automated hate speech detection and the problem of offensive language. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 11, No. 1).
18. Sap, M., Card, D., Gabriel, S., Choi, Y. and Smith, N.A., 2019, July. The risk of racial bias in hate speech detection. In Proceedings of the 57th annual meeting of the association for computational linguistics (pp. 1668-1678).
19. Kumar, S., Hamilton, W.L., Leskovec, J. and Jurafsky, D., 2018, April. Community interaction and conflict on the web. In Proceedings of the 2018 world wide web conference (pp. 933-943).
20. Ziems, C., He, B., Soni, S. and 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.
21. Tahmasbi, F., Schild, L., Ling, C., Blackburn, J., Stringhini, G., Zhang, Y. and Zannettou, S., 2020. " Go eat a bat, Chang!": On the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19. arXiv e-prints, pp.arXiv-2004.
22. Singh, L., Bansal, S., Bode, L., Budak, C., Chi, G., Kawintiranon, K., Padden, C., Vanarsdall, R., Vraga, E. and Wang, Y., 2020. A first look at COVID-19 information and misinformation sharing on Twitter. arXiv preprint arXiv:2003.13907.
23. Xinyue Shen, Xinlei He, Michael Backes, Jeremy Blackburn, Savvas Zannettou, Yang Zhang. On Xing Tian and the Perseverance of Anti-China Sentiment Online. In International Conference on Web and Social Media (ICWSM 2022)

 

 

Schedule

 

02.05:

1. Yiting Qu, A quantitative approach to understanding online antisemitism.

2. Ziqing Yang, Automated hate speech detection and the problem of offensive language

 

09.05:

3. Schmitt, John. You Can’t Stay Here: The Efficacy of Reddit’s 2015 Ban Examined Through Hate Speech

 

16.05:

5.  Soni, Varun  Does Platform Migration Compromise Content Moderation? Evidence from r/The_Donald and r/Incels.

6. Zeyang Sha,   The spread of true and false news online

 

23.05:

7. Drießler, Franziska  Disinformation on the Web: Impact, Characteristics, and Detection of Wikipedia Hoaxes

8. Welter, Alisa.  Who Let The Trolls Out? Towards Understanding State-Sponsored Trolls

 

30.05:

9. Quach, Nina. The risk of racial bias in hate speech detection

10. Decker, Philip.  On microtargeting socially divisive ads: A case study of russia-linked ad campaigns on facebook

 

13.06:

11. Kamp, Julius. " You Know What to Do" Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks

12. Burly, Keerthana Krishnamurthy.  Spread of hate speech in online social media

 

20.06:

13. Rao, Kavu Maithri. Community interaction and conflict on the web

14. Laichner, Julia. Auditing radicalization pathways on youtube.

 

27.06:

15. Chase, Alice. Examining the alternative media ecosystem through the production of alternative narratives of mass shooting events on Twitter.

4. Yixin Wu, On Xing Tian and the Perseverance of Anti-China Sentiment Online