User Behavior Modeling and Analysis

• {Mislove07} Alan Mislove, Massilmiliano Marcon, Krishna P. Gummadi, Peter Druschel, Bobby Bhattacharjee. Measurement and Analysis of Online Social Networks. In Proc. of ACM IMC, 2007. Flickr, Youtube, LiveJournal, Orkut; degree - power-law networks; densely connected core
• {Ahn07} Y. Ahn, S. Han, H. Kwak, S. Moon, and H. Jeong, Analysis of Topological Characteristics of Huge Online Social Networking Services. In Proc. of WWW, 2007. Cyworld, Myspace, Orkut; Cyworld - a changing scaling behavior over time in degree distribution
• {Chun08} Hyunwoo Chun, Haewoon Kwak, Young-Ho Eom, Yong-Yeol Ahn, Sue Moon, Hawoong Jeong. Comparison of Online Social Relations in Terms of Volume vs. Interaction: A Case Study of Cyworld. In Proc. of ACM IMC, 2008.
• {Cha09} Meeyoung Cha, Alan Mislove, and Krishna P. Gummadi. A Measurement-driven Analysis of Information Propagation in the Flickr Social Network. In Proceedings of the 18th Annual World Wide Web Conference (WWW'09), Madrid, Spain, April 2009.
• {Mislove10} Alan Mislove, Bimal Viswanath, Krishna P. Gummadi, Peter Druschel. You Are Who You Know: Inferring User Profiles in Online Social Networks. Proc. of ACM WSDM, 2010. infer user profile attributes
• {Tang11} Siyu Tang, Norbert Blenn, Christian Doerr, and Piet Van Mieghem. Digging in the Digg Social News Website. IEEE TRANSACTIONS ON MULTIMEDIA, 2011, 13(5):1163-1175.
• {Gong12} Neil Zhenqiang Gong, Wenchang Xu, et al. Evolution of Social-Attribute Networks: Measurements, Modeling, and Implications using Google+. Proc. of ACM IMC, 2012. Social-Attribute Networks (SAN)
• {Goncalves13} P. Goncalves, M. Araujo, F. Benevenuto, and M. Cha. Comparing and Combining Sentiment Analysis Methods. Proc. of ACM COSN, 2013. sentiment analysis
• {Ottoni13} R. Ottoni, J.P. Pesce, et al. Ladies First: Analyzing Gender Roles and Behaviors in Pinterest. Proc. of AAAI ICWSM, 2013. gender-based analysis of Pinterest (BFS-based crawling, 9.30% of the network)
• {Zhong13} Zhong, Changtao, Sunil Shah, Karthik Sundaravadivelan, and Nishanth Sastry. Sharing the Loves: Understanding the How and Why of Online Content Curation. Proc. of AAAI ICWSM, 2013. Social curation
• {Gilbert13} Eric Gilbert, Saeideh Bakhshi, et al. “I Need to Try This!”: A Statistical Overview of Pinterest. Proc. of ACM CHI, 2013. planetlab-based crawling, adding small integers to the identifier in a pin’s URL would find new pins created slightly later
• {Hu14} Yuheng Hu, Lydia Manikonda, Subbarao Kambhampati. What We Instagram: A First Analysis of Instagram Photo Content and User Types. Proc. of AAAI ICWSM, 2014.
• {Han14} Jinyoung Han, Daejin Choi, Byung-Gon Chun, et al. Collecting, Organizing, and Sharing Pins in Pinterest: Interest-driven or Social-driven? Proc. of ACM SIGMETRICS, 2014. pin propagation in Pinterest is mostly driven by pin's properties like its topic, not by user's characteristics like her number of followers [http://mmlab.snu.ac.kr/traces/pinterest/]]
• {Linder14} Linder, R., Snodgrass, C., and Kerne, A. Everyday Ideation: All of My Ideas Are On Pinterest, Proc. CHI 2014. interview-based study
• {Ma17} Xiao Ma, Jeff Hancock, Kenneth Lim Mingjie, and Mor Naaman. Self-disclosure and Perceived Trustworthiness of Airbnb Host Profiles. Proc. of ACM CSCW, 2017.
• {Wang17} Haoyu Wang, Zhe Liu, Yao Guo, Xiangqun Chen, Miao Zhang, Guoai Xu, Jason Hong. An Explorative Study of the Mobile App Ecosystem from App Developers’ Perspective. Proc. of WWW, 2017.
• {Eichstaedt18} Johannes C. Eichstaedt, Robert J. Smith, Raina M. Merchant, Lyle H. Ungar, Patrick Crutchley, Daniel Preoţiuc-Pietro, David A. Asch, H. Andrew Schwartz. Facebook language predicts depression in medical records. Proceedings of the National Academy of Sciences, 2018, 115(44):11203-11208. the content shared by consenting users on Facebook can predict a future occurrence of depression in their medical records