<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>2608</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>147</pageFirst>
    <pageLast>160</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Cham</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-03-08</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Modeling the Culture of Online Collaborative Groups with Affect Control Theory</title>
    <abstract language="eng">We review Affect Control Theory (ACT) as a promising basis for equipping computational agents in social simulations with a sense of sociality. ACT is a computational theory that integrates sociological insights about the symbolic construction of the social order with psychological knowledge about cognitive-affective mechanisms. After explaining the theoretical foundations of ACT and applications of the theory at the dyadic and group level, we describe a case study applying the theory from an ongoing research project examining self-organized online collaboration in software development.</abstract>
    <parentTitle language="eng">Advances in Social Simulation</parentTitle>
    <identifier type="isbn">978-3-030-61503-1</identifier>
    <identifier type="doi">10.1007/978-3-030-61503-1_14</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell -  Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Jonathan Howard Morgan</author>
    <author>Jun Zhao</author>
    <author>Nikolas Zöller</author>
    <author>Andrea Sedlacek</author>
    <author>Lena Chen</author>
    <author>Hayley Piper</author>
    <author>Yliana Beck</author>
    <author>Kimberly B. Rogers</author>
    <author>Jesse Hoey</author>
    <author>Tobias Schröder</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Culture</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Affect</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Gruppendynamik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kollaboration</value>
    </subject>
    <collection role="ddc" number="300">Sozialwissenschaften, Soziologie</collection>
    <collection role="institutes" number="">FB1 Sozial- und Bildungswissenschaften</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
    <thesisPublisher>Fachhochschule Potsdam</thesisPublisher>
  </doc>
  <doc>
    <id>3118</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>36</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>report</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups</title>
    <abstract language="eng">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.</abstract>
    <identifier type="doi">10.31235/osf.io/4hukx</identifier>
    <enrichment key="opus.import.date">2023-06-14T13:22:35+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">hisres</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Jesse Hoey</author>
    <author>Meiyappan Nagappan</author>
    <author>Kimberly B. Rogers</author>
    <author>Tobias Schröder</author>
    <author>Diego Dametto</author>
    <author>Nalin De Zoysa</author>
    <author>Rahul Iyer</author>
    <author>Jonathan H. Morgan</author>
    <author>Deepak Rishi</author>
    <author>Antonio D. Sirianni</author>
    <author>Seonghu Yun</author>
    <author>Jun Zhao</author>
    <author>Nikolas Zöller</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Computational social science</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>GitHub</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Gruppendynamik</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Sozialpsychologie</value>
    </subject>
    <collection role="ddc" number="300">Sozialwissenschaften</collection>
    <collection role="ddc" number="000">Informatik, Wissen, Systeme</collection>
    <collection role="institutes" number="">FB1 Sozial- und Bildungswissenschaften</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Fachhochschule Potsdam</thesisPublisher>
  </doc>
  <doc>
    <id>3373</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>23</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Complements and Competitors</title>
    <abstract language="eng">The vast majority of research on the diffusion of innovations focuses on how one particular idea or technology spreads across a network of connected individuals, or a population more generally. Diffusive processes are typically considered either in isolation. We consider innovations themselves as nodes in a larger network, and look at how individual innovations can spread with or against one another in a larger community of potential adopters.  Using a large publicly-available data set, custom-designed measurements, and network analysis methods, we present a temporal analysis of a set of technological innovations. Specifically, we examine how coding languages spread across users on GitHub, an online platform for collaborative coding. By looking at which languages co-appear in individual projects, we develop network based measurements of how frequently languages appear together in the same coding projects (functional cohesion), and how similar two languages are in terms of how often they co-appear with other languages in coding projects (functional equivalence). We also assess two types of diffusion, one form where users of one language become users of an additional language (complementary or 'piggybacking' diffusion), and another where users of one language abandon one language for another (competitive or 'cannibalistic' diffusion). Using MR-QAP Regression Techniques, we find strong evidence that functional cohesion positively predicts complementary diffusion. We also find some evidence that functional equivalence predicts competitive diffusion. More broadly, we find support for the idea that the networks of functional relationships between innovations is important for understanding diffusive processes.</abstract>
    <subTitle language="eng">The Co-functionality and Co-diffusion of Languages on a Collaborative Coding Platform</subTitle>
    <identifier type="doi">10.31235/osf.io/bfmy2</identifier>
    <enrichment key="opus.import.date">2024-02-20T12:33:42+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">hisres</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Antonio D. Sirianni</author>
    <author>Jonathan H. Morgan</author>
    <author>Nikolas Zöller</author>
    <author>Kimberly B. Rogers</author>
    <author>Tobias Schröder</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Soziologie</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kommunikation</value>
    </subject>
    <collection role="ddc" number="300">Sozialwissenschaften, Soziologie</collection>
    <collection role="institutes" number="">FB1 Sozial- und Bildungswissenschaften</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
    <collection role="Import" number="import">Import</collection>
    <collection role="open_access_fhp" number="">Diamond Open Access</collection>
    <thesisPublisher>Fachhochschule Potsdam</thesisPublisher>
  </doc>
  <doc>
    <id>3560</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>13</pageLast>
    <pageNumber/>
    <edition/>
    <issue>12</issue>
    <volume>3</volume>
    <type>article</type>
    <publisherName>Oxford University Press</publisherName>
    <publisherPlace>Oxford</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Complements and competitors</title>
    <abstract language="eng">Diffusive and contagious processes spread in the context of one another in connected populations. Diffusions may be more likely to pass through portions of a network where compatible diffusions are already present. We examine this by incorporating the concept of “relatedness” from the economic complexity literature into a network co-diffusion model. Building on the “product space” concept used in this work, we consider technologies themselves as nodes in “product networks,” where edges define relationships between products. Specifically, coding languages on GitHub, an online platform for collaborative coding, are considered. From rates of language co-occurrence in coding projects, we calculate rates of functional cohesion and functional equivalence for each pair of languages. From rates of how individuals adopt and abandon coding languages over time, we calculate measures of complementary diffusion and substitutive diffusion for each pair of languages relative to one another. Consistent with the principle of relatedness, network regression techniques (MR-QAP) reveal strong evidence that functional cohesion positively predicts complementary diffusion. We also find limited evidence that functional equivalence predicts substitutive (competitive) diffusion. Results support the broader finding that functional dependencies between diffusive processes will dictate how said processes spread relative to one another across a population of potential adopters.</abstract>
    <parentTitle language="eng">PNAS nexus</parentTitle>
    <subTitle language="eng">Examining technological co-diffusion and relatedness on a collaborative coding platform</subTitle>
    <identifier type="issn">2752-6542</identifier>
    <identifier type="doi">10.1093/pnasnexus/pgae549</identifier>
    <enrichment key="opus.import.date">2025-01-02T09:44:16+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">hisres</enrichment>
    <licence>Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International</licence>
    <author>Antonio D. Sirianni</author>
    <author>Jonathan H. Morgan</author>
    <author>Nikolas Zöller</author>
    <author>Kimberly B. Rogers</author>
    <author>Tobias Schröder</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Computational social science</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Innovation</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Netzwerk</value>
    </subject>
    <collection role="ddc" number="300">Sozialwissenschaften, Soziologie</collection>
    <collection role="institutes" number="">FB1 Sozial- und Bildungswissenschaften</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
    <collection role="Import" number="import">Import</collection>
    <collection role="open_access_fhp" number="">Gold Open Access</collection>
    <thesisPublisher>Fachhochschule Potsdam</thesisPublisher>
  </doc>
</export-example>
