- JM Hofman, A Sharma, DJ Watts. Prediction and explanation in social systems. Science, 2017.
- Exploring Limits to Prediction in Complex Social Systems. WWW 2016.
- M Gabielkov, A Rao, A Legout. Studying Social Networks at Scale: Macroscopic Anatomy of the Twitter Social Graph. SIGMETRICS 2014.
- BP Chamberlain, C Humby, MP Deisenroth. Detecting the Age of Twitter Users. arXiv:1601.04621.
- Standard Occupational Classification (SOC)
- L Sloan, J Morgan, P Burnap, M Williams. Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data. PLoS ONE 10(3): e0115545, 2015.
- M Ciot, M Sonderegger, D Ruths. Gender Inference of Twitter Users in Non-English Contexts. EMNLP 2013.
- D Jurgens et al. Geolocation Prediction in Twitter Using Social Networks: A Critical Analysis and Review of Current Practice. ICWSM 2015.
- R Compton, D Jurgens, D Allen. Geotagging One Hundred Million Twitter Accounts with Total Variation Minimization. Big Data, 2014.
- A Bassolas et al. Touristic site attractiveness seen through Twitter. arXiv:1601.07741.
- J McCorriston, D Jurgens, D Ruths. Organizations are Users Too: Characterizing and Detecting the Presence of Organizations on Twitter. ICWSM 2015.
- D Kim, Y Jo, I. Moon, A Oh. Analysis of twitter lists as a potential source for discovering latent characteristics of users. 2010.
- O DeMasi, D Mason, J Ma. Understanding Communities via Hashtag Engagement: A Clustering Based Approach. ICWSM 2016.
Diffusion, Cascades, Popularity
- C Li, J Ma, X Guo, Q Mei. DeepCas: an End-to-end Predictor of Information Cascades. WWW 2017.
- K Węgrzycki, P Sankowski, A Pacuk, P Wygocki. Why Do Cascade Sizes Follow a Power-Law?. WWW 2017.
- R Rotabi, K Kamath, J Kleinberg, A Sharma. Cascades: A view from Audience. WWW 2017.
- B Shulman, A Sharma, D Cosley. Predictability of Popularity: Gaps between Prediction and Understanding. ICWSM 2016.
- KH Chu et al. Diffusion of Messages from an Electronic Cigarette Brand to Potential Users through Twitter. PLoS ONE 10(12): e0145387, 2015.
- K Park et al. Persistent Sharing of Fitness App Status on Twitter. arXiv:1510.04049.
- M Beguerisse-Díaz et al. The 'who' and 'what' of #diabetes on Twitter. arXiv:1508.05764.
- EM Clark et al. Vaporous Marketing: Uncovering Pervasive Electronic Cigarette Advertisements on Twitter. PLoS ONE, 2016.
- SE Alajajian et al. The Lexicocalorimeter: Gauging public health through caloric input and output on social media. arXiv:1507.05098.
- S Goel, A Anderson, J Hofman, DJ Watts. The structural virality of online diffusion.
- S Wu et al. Who says what to whom on twitter. WWW 2011.
#### Scholarly (Science) Communication Bibliometrics, Scientometrics, Informetrics, Webometrics, Altmetrics... PHILOSOPHY IMPACT JM Kapp, B Hensel, KT Schnoring. Is Twitter a forum for disseminating research to health policy makers?. Annals of Epidemiology. C Sugimoto. “Attention is not impact" and other challenges for altmetrics. L Bornmann. Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics. Scientometrics 103(3): 1123-1144, 2015. S Haustein, R Costas, V Larivière. Characterizing Social Media Metrics of Scholarly Papers: The Effect of Document Properties and Collaboration Patterns. PLoS ONE 10(3): e0120495, 2015. R García et al. Language, Twitter and Academic Conferences. arXiv:1504.03374. Scientists share inspiration on Twitter with #IAmAScientistBecause and #BeyondMarieCurie. The Economics Twitosphere Top 100 Influential Users: An Algorithmic Approach. C Woolston. Scientists are cautious about public outreach. Nature 518: 459, 2015 M Baker. Social media: A network boost. Nature, 518:263-265, 2015. AT Hadgu, R Jäschke. Identifying and Analyzing Researchers on Twitter. In Proc. WebSci 2014. K Weller, C Puschmann. Twitter for Scientific Communication: How Can Citations/References be Identified and Measured?. In Proc. WebSci 2011. K Weller, E Dröge, C Puschmann. Citation Analysis in Twitter: Approaches for Defining and Measuring Information Flows within Tweets during Scientific Conferences. In Proc. the ESW2011 workshop on making sense of microposts.
#### Brands and Marketing on Twitter S Lehrer, T Xie. Box Office Buzz: Does Social Media Data Steal the Show from Model Uncertainty When Forecasting for Hollywood?. NBER WP, 2016. P Adamopoulos, V Todri. The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events. KDD 2015. MJ Culnan, PJ McHugh, JI Zubillaga. How Large U.S. Companies Can Use Twitter and Other Social Media to Gain Business Value. MIS Quarterly Executive, 2010. ES Kwon, Y Sung. Follow Me! Global Marketers' Twitter Use. Journal of Interactive Advertising, 2011. [Anthropomorphism of brand accounts] JS Lin, J Peña. Are You Following Me? A Content Analysis of TV Networks' Brand Communication on Twitter. Journal of Interactive Advertising, 2011. [Bales's interaction process analysis] * M Vernuccio. Communicating Corporate Brands Through Social Media: An Exploratory Study. International Journal of Business Communication, 2014.
- EM Clark et al. Sifting Robotic from Organic Text: A Natural Language Approach for Detecting Automation on Twitter. arXiv:1505.04342.
- J Messias, L Schmidt, R Oliveira, F Benevenuto. You followed my bot! Transforming robots into influential users in Twitter. First Monday, 2013.
- J Golbeck. Benford's Law Applies To Online Social Networks. arXiv:1504.04387.
Finding Street Gang Members on Twitter. ASONAM, 2016.
- C Buntain, J Lin, J Golbeck. Learning to Discover Key Moments in Social Media Streams. arXiv:1508.00488.
- K Garimella et al. Quantifying Controversy in Social Media. arXiv:1507.05224. [This Is What Controversies Look Like in the Twittersphere.]
- YH Eom et al. Twitter-based analysis of the dynamics of collective attention to political parties. arXiv:1504.06861.
- DB Kurka, A Godoy, FJ Von Zuben. Online Social Network Analysis: A Survey of Research Applications in Computer Science. arXiv:1504.05655.