PRIVACY IN SOCIAL COMPUTING

Much of our recent work in privacy is about so-called self-disclosure, or individual's decision to share personal information with an audience. We study this phenomenon online.  This work involves development of new approaches in machine learning to detect and label instances of self-disclosure, as well as data-driven work understanding contextual and peer influences on this behavior. 

Through the NSF RAPID program, we are now also studying the impacts of COVID-19 on user privacy decisions on social media.  This work is informed by machine learning, natural language processing, game theory, network science and ethics.

 

  • J. Lee, S. Rajtmajer, E. Srivatsavaya, S. Wilson. Digital inequality through the lens of self-disclosure. Proceedings on Privacy Enhancing Technologies (PoPETS), July 2021.

  • P. Umar, A. Squicciarini, S. Rajtmajer. A Study of Self-Privacy Violations in Online Public Discourse. IEEE Big Data, December 2020.

  • C. Akiti, S. Rajtmajer, A. Squicciarini. A Semantics-based Approach to Disclosure Classification in User-Generated Online Content. Findings of The Conference on Empirical Methods in Natural Language Processing (EMNLP), November 2020.

  • C. Akiti, S. Rajtmajer, A. Squicciarini. Contextual Representation of Self-Disclosure and Supportivenss in Short Text. Shared Task Paper. The AAAI-20 Workshop on Affective Content Analysis (AFFCON), January 2020. 

  • H. Zhong, H. Li, A. Squicciarini, S. Rajtmajer, D. Miller. Toward Image Privacy Classification and Spatial Attribution of Private Content. IEEE International Conference on Big Data, December 2019. 

  • C. Griffin, S. Rajtmajer, P. Umar, A. Squicciarini. Power Law Public Goods Game for Personal Information Sharing in News Commentaries. Conference on Decision and Game Theory for Security (GAMESEC), October 2019. 

  • P. Umar, A. Squicciarini, S. Rajtmajer. Detection and Analysis of Self-Disclosure in Online News Commentaries. The Web Conference (WWW), May 2019.

  • A. Squicciarini, S. Rajtmajer, N. Zannone. Multi-Party Access Control: Requirements, State of the Art and Open Challenges. Symposium on Access Control Models and Technologies (SACMAT) 2018: 49.

  • S. Rajtmajer, A. Squicciarini, J. Such, J. Semonsen, and A. Belmonte. An Ultimatum Game Model for the Evolution of Privacy in Jointly Managed Content. Conference on Decision and Game Theory for Security (GAMESEC), October 2017.

  • C. Griffin, S. Rajtmajer, and A. Squicciarini.  A Model of Paradoxical Privacy Behavior (Invited paper). International Conference on Collaboration and Internet Computing (IEEE CIC), October 2016.

  • A. Tyagi, A. Squicciarini, S. Rajtmajer, C. Griffin. An In-Depth Study of Peer Influence on Collective Decision Making for Multi-party Access Control (Invited Paper). International Conference on Information Reuse and Integration (IEEE ICI), July 2016.

  • S. Rajtmajer, C. Griffin and A. Squicciarini. Constrained Social-Energy Minimization for Multi- Party Sharing in Online Social Networks. International Conference on Autonomous and Multiagent Systems (AAMAS), Singapore, May 2016.

  • S. Rajtmajer, C. Griffin and A. Squicciarini. Determining a Discrete Set of Site-Constrained Privacy Options for Users in Social Networks through Stackelberg Games. Conference on Decision and Game Theory for Security (GAMESEC), London, UK, November 2015.

  • C. Griffin, A. Squicciarini, S. Rajtmajer, M. Tentilucci and S. Lin. Site-Constrained Privacy Options for Users in Social Networks through Stackelberg Games. In Proc. Sixth ASE International Conference on Social Computing, May 2014.

©2020 Sarah Rajtmajer, PhD