- Bit by Bit - Salganik
- Decoding the Social World - González-Bailón (Video)
- Oxford Handbook of Networked Communication - Foucault Welles and González-Bailón
- "Computational Social Science" - Lazer, Pentland, Adamic, Aral, Barabasi, Brewer, Christakis, Contractor, Fowler, Gutmann, Jebara, King, Macy, Roy, and Van Alstyne (2009)
- "The cultural environment: measuring culture with big data" - Bail (2014)
- "Social science in the era of big data" - González‐Bailón (2013)
- "Computational Social Science ≠ Computer Science + Social Data" - Wallach (2018)
- "Critical Questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon" - boyd and Crawford (2012)
- "Private traits and attributes are predictable from digital records of human behavior" - Kosinski, Stillwell, and Graepel (2013)
- "Digital Footprints: Opportunities and Challenges for Online Social Research" - Golder and Macy (2014)
- "Computational social science: Obstacles and opportunities" - Lazer et. al. (2020)
- "Computational Social Science and the Study of Political Communication" - Theocharis and Jungherr (2020)
- "The empiricist’s challenge: Asking meaningful questions in political science in the age of big data" - Jungherr and Theocharis (2017)
- Do social rewards lead to an increase in participation on Wikipedia?
- Does exposure to opposing political views increase political polarization?
- Do cues on social media...
- Do early advantages lead to further inequality in the consumption of music?
- Can mental representation processes explain cultural emergence?
- What factors influence police behavior?
- How do groups organize on social media?
- "Hijacking #MYNYPD: Social Media Dissent and Networked Counterpublics" - Jackson and Foucault Welles (2015)
- "#Ferguson is everywhere: initiators in emerging counterpublic networks" - Jackson and Foucault Welles (2015)
- "Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter" - Gallagher, Reagan, Danforth, and Dodds (2018)
- "The Dynamics of Protest Recruitment through an Online Network" - González-Bailón, Borge-Holthoefer, Rivero, and Moreno (2011)
- "Broadcasters and Hidden Influentials in Online Protest Diffusion" - González-Bailón, Borge-Holthoefer, and Moreno (2013)
- How do liberal and conservative blogs link to one another?
- Can we identify friendship relations from communication trace data?
- What can network structure tell us about institutional gender imabalances?
- What can network structure tell us about how we participate in online dating?
- Do choices of who to follow on Twitter reveal ideological preferences?
- Do choices of which pages to like on Facebook reveal ideological preferences?
- Does the use of language refelect emotional states?
- "Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents - Dodds and Danforth (2010)
- "Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures" - Golder and Macy (2011)
- "Twitter mood predicts the stock market" - Bollen, Mao, and Zeng (2011)
- Are there problems with how we use social-media to infer ideological preferences?
- Do online behaviors lead to diversity in the news we are exposed to and consume?
- Are digital platforms biased?
- "The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections" - Epstein and Robertson (2015)
- "Auditing local news presence on Google News" - Fischer, Jaidka, and Lelkes (2020)
- "Auditing Partisan Audience Bias within Google Search" - Robertson et. al. (2018)
- "Auditing the Personalization and Composition of Politically-Related Search Engine Results Pages" - Robertson, Lazer, and Wilson (2018)
- What are the consequences of algorithmic decision making?
- How can we measure economic impacts?
- How do governments censor their citizens?
- Can we use the questions asked of athletes to identify subtle gender biases?
- Can social media posts show that counselling strategies are working following tragedies?
- Can language reveal how boring politicans are?
- Does language reflect political partisanship and polarization?
- How do emotions affect political attitudes?
- "The Science of Culture? Social Computing, Digital Humanities and Cultural Analytics" - Manovich (2016)
- "There Will Be Numbers" - Piper (2016)
- Do literary genres experience cyclical popularity?
- Can we identify and classify literary genres using computational methods?
- How are some scholars using computational methods to study identity?
- What should we do when we have missing data?
- How can we use data science to implement political science methods?
- What purpose do models serve?
- Which text methods are best in which contexts?
- How can we combine data sources?
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What are some examples that are ethically dubious or outright bad?
- What is going to happen when we lose access to some data?
- Are big data biased and, if so, how?
- Could a popular data source be deeply flawed?
- "Caveat emptor, computational social science: Large-scale missing data in a widely-published Reddit corpus" - Gaffney and Matias (2018)
- "Social media for large studies of behavior" - Ruths and Pfeffer (2014)
- "Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls" - Tufekci (2014)
- "Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election" - Meng (2018)
- How should we collect our data?
- How should we document our data?