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1. Representing Real-Time Multi-User Collaboration in Visualizations

   Neogy, Rupayan; Zong, Jonathan; Satyanarayan, Arvind. (October 2020, IEEE Visualization (VIS) Conference)

   null (Ed.)

   Establishing common ground and maintaining shared awareness amongst participants is a key challenge in collaborative visualization. For real-time collaboration, existing work has primarily focused on synchronizing constituent visualizations - an approach that makes it difficult for users to work independently, or selectively attend to their collaborators' activity. To address this gap, we introduce a design space for representing synchronous multi-user collaboration in visualizations defined by two orthogonal axes: situatedness, or whether collaborators' interactions are overlaid on or shown outside of a user's view, and specificity, or whether collaborators are depicted through abstract, generic representations or through specific means customized for the given visualization. We populate this design space with a variety of examples including generic and custom synchronized cursors, and user legends that collect these cursors together or reproduce collaborators' views as thumbnails. To build common ground, users can interact with these representations by peeking to take a quick look at a collaborator's view, tracking to follow along with a collaborator in real-time, and forking to independently explore the visualization based on a collaborator's work. We present a reference implementation of a wrapper library that converts interactive Vega-Lite charts into collaborative visualizations. We find that our approach affords synchronous collaboration across an expressive range of visual designs and interaction techniques. 

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2. Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups

   Jesse Hoey, Meiyappan Nagappan (January 2021, SocArXiv)

   null (Ed.)

   Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data. 

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3. Perceptions of open‐source software developers on collaborations: An interview and survey study

   https://doi.org/10.1002/smr.2393  

   Constantino, Kattiana; Souza, Mauricio; Zhou, Shurui; Figueiredo, Eduardo; Kästner, Christian (October 2021, Journal of Software: Evolution and Process)

   With the emergence of social coding platforms, collaboration has become a key and dynamic aspect to the success of software projects. In such platforms, developers have to collaborate and deal with issues of collaboration in open-source software development. Although collaboration is challenging, collaborative development produces better software systems than any developer could produce alone. Several approaches have investigated collaboration challenges, for instance, by proposing or evaluating models and tools to support collaborative work. Despite the undeniable importance of the existing efforts in this direction, there are few works on collaboration from perspectives of developers. In this work, we aim to investigate the perceptions of open-source software developers on collaborations, such as motivations, techniques, and tools to support global, productive, and collaborative development. Following an ad hoc literature review, an exploratory interview study with 12 open-source software developers from GitHub, our novel approach for this problem also relies on an extensive survey with 121 developers to confirm or refute the interview results. We found different collaborative contributions, such as managing change requests. Besides, we observed that most collaborators prefer to collaborate with the core team instead of their peers. We also found that most collaboration happens in software development (60%) and maintenance (47%) tasks. Furthermore, despite personal preferences to work independently, developers still consider collaborating with others in specific task categories, for instance, software development. Finally, developers also expressed the importance of the social coding platforms, such as GitHub, to support maintainers, and contributors in making decisions and developing tasks of the projects. Therefore, these findings may help project leaders optimize the collaborations among developers and reduce entry barriers. Moreover, these findings may support the project collaborators in understanding the collaboration process and engaging others in the project. 

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4. Dynamic Games Among Teams with Delayed Intra-Team Information Sharing

   https://doi.org/10.1007/s13235-022-00424-4  

   Tang, Dengwang; Tavafoghi, Hamidreza; Subramanian, Vijay; Nayyar, Ashutosh; Teneketzis, Demosthenis (February 2022, Dynamic Games and Applications)

   We analyze a class of stochastic dynamic games among teams with asymmetric information, where members of a team share their observations internally with a delay of d. Each team is associated with a controlled Markov Chain, whose dynamics are coupled through the players’ actions. These games exhibit challenges in both theory and practice due to the presence of signaling and the increasing domain of information over time. We develop a general approach to characterize a subset of Nash equilibria where the agents can use a compressed version of their information, instead of the full information, to choose their actions. We identify two subclasses of strategies: sufficient private information-Based (SPIB) strategies, which only compress private information, and compressed information-based (CIB) strategies, which compress both common and private information. We show that SPIB-strategy-based equilibria exist and the set of payoff profiles of such equilibria is the same as that of all Nash equilibria. On the other hand, we show that CIB-strategy-based equilibria may not exist. We develop a backward inductive sequential procedure, whose solution (if it exists) provides a CIB strategy-based equilibrium. We identify some instances where we can guarantee the existence of a solution to the above procedure. Our results highlight the tension among compression of information, ability of compression-based strategies to sustain all or some of the equilibrium payoff profiles, and backward inductive sequential computation of equilibria in stochastic dynamic games with asymmetric information. 

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5. Investigating Researchers’ Motivations and Identities through Convergent Learning from Divergent Perspectives

   https://doi.org/10.1109/FIE43999.2019.9028364  

   Pelan, Renee Rigrish; Kajfez, Rachel Louis (October 2019, 2019 IEEE Frontiers in Education Conference (FIE))

   This Research Work-in-Progress paper explores how motivation and identity can evolve when faculty from different disciplines (arts, engineering, medicine, etc.) collaborate to present on a central theme or topic (e.g. color) across multiple community settings. Sharing research findings beyond the academic community is essential for systemic change and wide spread enhancements to our everyday lives. Through this work, we explore how faculty researchers’ motivations to share their work and their identities as researchers develop through collaborative experiences with other faculty that aim at sharing research findings with the public. In this study, faculty from divergent academic fields are working together to present convergent presentations as one coherent theme across three different informal learning sessions as well as a control setting. These presentations intend to increase public engagement with scientific research and broaden the scope of Science, Technology, Engineering, and Math (STEM) learning by approaching the themes through the faculty’s different academic backgrounds. Through collaboration and engagement with the public, we will track how faculty’s identities as researchers and motivations to share their work develop over this experience through the use of the Longitudinal Model of Motivation and Identity (LMMI). Over the course of this study, we hope to see gains in faculty motivation and researcher identities who engage with the public through this experience. For this paper, we focus on framing the overall study and provide initial findings from our recruitment survey. 

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