<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>2606</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Taylor and Francis</publisherName>
    <publisherPlace>London</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-03-07</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Friend or Foe: A Review and Synthesis of Computational Models of the Identity Labeling Problem</title>
    <abstract language="eng">We introduce the identity labeling problem – given an individual in a social situation, can we predict what identity(ies) they will be labeled with by someone else? This problem remains a theoretical gap and methodological challenge, evidenced by the fact that models of social-cognition often sidestep the issue by treating identities as already known. We build on insights from existing models to develop a new framework, entitled Latent Cognitive Social Spaces, that can incorporate multiple social cues including sentiment information, socio-demographic characteristics, and institutional associations to estimate the most culturally expected identity. We apply our model to data collected in two vignette experiments, finding that it predicts identity labeling choices of participants with a mean absolute error of 10.9%, a 100% improvement over previous models based on parallel constraint satisfaction and affect control theory.</abstract>
    <parentTitle language="eng">The Journal of Mathematical Sociology</parentTitle>
    <identifier type="doi">10.1080/0022250X.2021.1923016</identifier>
    <identifier type="issn">1545-5874</identifier>
    <identifier type="arxiv">2105.04462v1</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>Kenneth Joseph</author>
    <author>Jonathan Howard Morgan</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Soziale Identität</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Computational social science</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Analytische Soziologie</value>
    </subject>
    <collection role="ddc" number="300">Sozialwissenschaften, Soziologie</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
    <thesisPublisher>Fachhochschule Potsdam</thesisPublisher>
  </doc>
</export-example>
