Abilov, A., Yiqing Hua, Hana Matatov, Ofra Amir, and M. Naaman. 2021. “VoterFraud2020: a Multi-modal Dataset of Election Fraud Claims on Twitter.” ICWSM.
Shraga, Roee, Ofra Amir, and Avigdor Gal. 2021. “Learning to Characterize Matching Experts.” 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1236–1247. IEEE.
Huber, Tobias, Katharina Weitz, Elisabeth André, and Ofra Amir. 2021. “Local and global explanations of agent behavior: Integrating strategy summaries with saliency maps.” Artificial Intelligence 301. Elsevier: 103571.
Shalala, Rafael, Ofra Amir, and Ido Roll. 2021. “Towards Asynchronous Data Science Invention Activities at Scale.” International Society of the Learning Sciences (ISLS’21).
Gilad, Zohar, Ofra Amir, and Liat Levontin. 2021. “The Effects of Warmth and Cometence Perceptions on Users' Choice of an AI System.” ACM SIGCHI. Pre-print
Lin, Jody L, Catherine L Clark, Bonnie Halpern-Felsher, Paul N Bennett, Shiri Assis-Hassid, Ofra Amir, Yadira Castaneda Nunez, et al. 2020. “Parent Perspectives in Shared Decision-Making for Children With Medical Complexity.” Academic Pediatrics 20 (8). Elsevier: 1101–1108.
Amir, Ofra, Finale Doshi-Velez, and David Sarne. 2019. “Summarizing agent strategies.” Autonomous Agents and Multi-Agent Systems 33 (5). Springer: 628–644.
Lage*, Isaac, Daphna Lifschitz*, Finale Doshi-Velez, and Ofra Amir. 2019. “Exploring Computational User Models for Agent Policy Summarization.” IJCAI'19. Macao, China.
Amir, Ofra, Barbara J. Grosz, Krzysztof Z. Gajos, and Limor Gultchin. 2019. “Personalized Change Awareness: Reducing Information Overload in Loosely-Coupled Teamwork.” Artificial Intelligence. preprint
Matatov, Hana, Adina Bechhofer, Lora Aroyo, Ofra Amir, and Mor Naaman. 2018. “DejaVu: A System for Journalists to Collaboratively Address Visual Misinformation.” Computation + Journalism Symposium. Miami, FL. Authors' Version
Cohensius, Gal, Omer Ben Porat, Reshef Meir, and Ofra Amir. 2018. “Efficient Crowdsourcing via Proxy Voting .” COMSOC'18. Authors' Version
Amir, Ofra, Finale Doshi-Velez, and David Sarne. 2018. “Agent Strategy Summarization.” the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018 blue sky track). Stockholm, Sweden. Authors' Version
Amir, Dan, and Ofra Amir. 2018. “HIGHLIGHTS: Summarizing Agent Behaviors to People.” the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018). Stockholm, Sweden. Authors' Version
Amir, Ofra, Ece Kamar, Andrey Kolobov, and Barbara Grosz. 2016. “Interactive Teaching Strategies for Agent Training.” IJCAI. New York City, USA. [pdf]
Amir, Ofra, Barbara Grosz, and Krzysztof Gajos. 2016. “Mutual Influence Potential Networks: Enabling Information Sharing in Loosely-Coupled Extended-Duration Teamwork.” IJCAI. New York City, USA. [pdf]
Amir, Ofra, Barbara Grosz, and Krzysztof Gajos. 2016. “MIP-Nets: Enabling Information Sharing in Loosely-Coupled Teamwork.” AAAI 2016 Student Abstracts. preprint Abstract

People collaborate in carrying out such complex activities as
treating patients, co-authoring documents and developing software.
While technologies such as Dropbox and Github enable
groups to work in a distributed manner, coordinating team
members’ individual activities poses significant challenges. In
this paper, we formalize the problem of “information sharing
in loosely-coupled extended-duration teamwork”. We develop
a new representation, Mutual Influence Potential Networks
(MIP-Nets), to model collaboration patterns and dependencies
among activities, and an algorithm, MIP-DOI, that uses this
representation to reason about information sharing.

Gehrmann, Sebastian, Lauren Urke, Ofra Amir, and Barbara J Grosz. 2015. “Deploying AI Methods to Support Collaborative Writing: a Preliminary Investigation.” CHI'15 Extended Abstracts on Human Factors in Computing Systems. ACM. preprint Abstract

Many documents (e.g., academic papers, government reports) are typically written by multiple authors. While existing tools facilitate and support such collaborative efforts (e.g., Dropbox, Google Docs), these tools lack intelligent information sharing mechanisms. Capabilities such as "track changes" and "diff"" visualize changes to authors, but do not distinguish between minor and major edits and do not consider the possible effects of edits on other parts of the document. Drawing collaborators' attention to specific edits and describing them remains the responsibility of authors. This paper presents our initial work toward the development of a collaborative system that supports multi-author writing. We describe methods for tracking paragraphs, identifying significant edits, and predicting parts of the paper that are likely to require changes as a result of previous edits. Preliminary evaluation of these methods shows promising results.

Amir, Ofra, Barbara Grosz, Krzysztof Gajos, Sonja Swenson, and Lee Sanders. 2015. “From Care Plans to Care Coordination: Opportunities For Computer Support of Teamwork in Complex Healthcare.” Proceedings of CHI'15 [honorable mention] (to appear). Preprint Abstract

Children with complex health conditions require care from a large, diverse team of caregivers that includes multiple types of medical professionals, parents and community support organizations. Coordination of their outpatient care, essential for good outcomes, presents major challenges. Extensive healthcare research has shown that the use of integrated, team-based care plans improves care coordination, but such plans are rarely deployed in practice. This paper reports on a study of care teams treating children with complex conditions at a major university tertiary care center. This study investigated barriers to plan implementation and resultant care coordination problems. It revealed the complex nature of teamwork in complex care, which poses challenges to team coordination that extend beyond those identified in prior work and handled by existing coordination systems.

The paper builds on a computational teamwork theory to identify opportunities for technology to support increased plan-based complex-care coordination and to propose design approaches for systems that enable and enhance such coordination.