Reading List

Introduction to disinformation readings:

• Quick introduction to terminology used across the field: https://mediawell.ssrc.org/literature-reviews/defining-disinformation/versions/1-0/
• Disinformation as collaborative work: https://dl.acm.org/doi/abs/10.1145/3359229
• How right-wing media shapes the information ecosystem: https://www.cjr.org/analysis/breitbart-media-trump-harvard-study.php
• Full article: https://dash.harvard.edu/bitstream/handle/1/33759251/2017-08_electionReport_0.pdf
• Media manipulation - actors, tactics, motivations: https://datasociety.net/wp-content/uploads/2017/05/DataAndSociety_MediaManipulationAndDisinformationOnline-1.pdf
• What is the harm of disinformation? Thinking about the direct effects of exposure to disinformation vs the second order effects on the public: https://mediawell.ssrc.org/expert-reflections/on-digital-disinformation-and-democratic-myths/

Technical readings:

• Measuring prevalence of low-quality information: https://arxiv.org/pdf/2004.14484.pdf
• LIME Paper

Advanced readings:

• Disinformation domain discovery: https://arxiv.org/pdf/2003.07684.pdf
• Measuring the behavioral effects of exposure to disinformation: https://bfi.uchicago.edu/wp-content/uploads/BFI_WP_202044.pdf
• Russian tactics: https://dataspace.princeton.edu/jspui/handle/88435/dsp01fb494c31z
• Lifecycle of media manipulation: https://datajournalism.com/read/handbook/verification-3/investigating-disinformation-and-media-manipulation/the-lifecycle-of-media-manipulation
• Understanding the proliferation of disinformation as an active, sociotechnical process as opposed to the “silver bullet” theory that dominated early research on propaganda: https://georgetownlawtechreview.org/wp-content/uploads/2018/07/2.2-Marwick-pp-474-512.pdf
• Text classification with few examples: https://arxiv.org/pdf/2005.08469.pdf
• Exploiting class labels for text classification: https://arxiv.org/pdf/2006.02104.pdf

Other Readings

• Introduction to GDI and the ideas that launched their work (some of this has changed but the core ideas are the same)

• Short introduction to programmatic ad buying

• Managing bias in algorithms that regulate online content

• Brief history of dominant frameworks for thinking about regulating online content

• Facebook Artificial Intelligence.“Using AI to Detect COVID-19 Misinformation and Exploitative Content.” Facebook Artificial Intelligence, May 12, 2020.

• Kompella, Kashyap. “Can Machine Learning Help Fight Fake News?” EContent, September 1, 2017.

• Towards automatically filtering fake news in Portuguese

• Disinformation Detection: A review of linguistic feature selection and classification models in news veracity assessments

• Fake news, rumor, information pollution in social media and web: A contemporary survey of state-of-the-arts, challenges and opportunities

• Detecting click-bait headlines https://www-sciencedirect-com.ezproxy.cul.columbia.edu/science/article/pii/S1877050918318210

• Fake News Detection using Bi-directional LSTM-Recurrent Neural Network.

• Fake News Early Detection: A Theory-driven Model

• Measuring and Mitigating Unintended Bias in Text Classification

• Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking https://homes.cs.washington.edu/~hrashkin/factcheck.html

• Improving Generalizability of Fake News Detection Methods using Propensity Score Matching

• https://public.oed.com/blog/corpus-analysis-of-the-language-of-covid-19/