Data-driven Understanding of the Disinformation Epidemic

Dear all,

After receiving your responses, we have arranged a schedule for you to give the presentations (see it at the end of this message).

The presentation starts on 8th May. Every Monday from 4 pm to 5 pm, we will have two presenters introduce their preferred papers.

See you on the 8th of May :)

Best,
Xinyue

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08.05.2023:

1. Taha Murtaza Gain, On Xing Tian and the Perseverance of Anti-China Sentiment Online.
2. Oliver Dorr, Evolution of the Manosphere Across the Web.

 

15.05.2023:

3. Mohammad Munem Shahriar, On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning.
4. Michael Gallinger, SoK: Hate, Harassment, and the Changing Landscape of Online Abuse.

 

22.05.2023: 
5. Animesh Kumar Aashu, Fact-Checking Meets Fauxtography: Verifying Claims About Images.
6. Sana Athar, (Mis) information dissemination in WhatsApp: Gathering, analyzing and countermeasures.

 

05.06.2023: 
7. Hendrik Suhr, "It is just a flu": Assessing the Effect of Watch History on YouTube's Pseudoscientific Video Recommendations.
8. Yukun Jiang, Understanding and Evaluating Racial Biases in Image Captioning.

 

12.06.2023: 
9. Khadija Butt, Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots.
10. Malal Rachih, Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions.
 

Dear all,

The paper list is online, please select three papers (ranked by preference) and send them to Xinyue Shen (xinyue.shen@cispa.de) by today (25.04.2023) 23:59.

Note that the assignment will be based on the first-come, first-served principle.

The assignment will be informed tomorrow 1 pm.

Best,

Xinyue

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Paper list

1. On Xing Tian and the Perseverance of Anti-China Sentiment Online.

2. SoK: Hate, Harassment, and the Changing Landscape of Online Abuse.

3. On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning.

4. Understanding and Detecting Hateful Content using Contrastive Learning.

5. The Evolution of the Manosphere Across the Web.

6. (Mis) information dissemination in WhatsApp: Gathering, analyzing and countermeasures.

7. "It is just a flu": Assessing the Effect of Watch History on YouTube's Pseudoscientific Video Recommendations.

8. Understanding the Use of Fauxtography on Social Media.

9. Fact-Checking Meets Fauxtography: Verifying Claims About Images.

10. Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots.

11. Challenges in Detoxifying Language Models.

12. Anticipating Safety Issues in e2e Conversational AI: Framework and Tooling.

13. Towards Understanding and Mitigating Social Biases in Language Models.

14. Automatically Auditing Large Language Models via Discrete Optimization.

15. Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

16. Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP.

17. Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions

18. Understanding and Evaluating Racial Biases in Image Captioning.

19. DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers.

20. Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models.

21. DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Diffusion Models.

22. DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks.