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    <id>3984</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>675</pageFirst>
    <pageLast>698</pageLast>
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    <edition/>
    <issue>3</issue>
    <volume>84</volume>
    <type>article</type>
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    <completedDate>2021-01-19</completedDate>
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    <title language="eng">Do Online Voter Guides Empower Citizens? Evidence from a Field Experiment with Digital Trace Data</title>
    <abstract language="eng">Voting Advice Applications (VAAs), which provide citizens with information on the party that best represents their political preferences, are often cited as evidence of the empowering capabilities of digital tools. Aside from the informational benefits of these voter guides, observational studies have suggested a strong effect on political participation and vote choice. However, existing impact evaluations have been limited by a reliance on convenience samples, lack of random assignment, or both. This raises questions about self-selection and the precise mechanisms underlying how voters learn about politics. Here, we provide evidence from a field experiment with survey outcomes conducted with a sample of over 1,000 German citizens in the 2017 federal election campaign. Using linked panel survey and digital trace data combined with a randomized encouragement to complete a VAA, we assess respondents’ compliance with treatment and observe how the use of this tool affects political behavior, attitudes, media consumption, political knowledge, and even social media activity. Our findings reveal that the overwhelming consensus in favor of positive effects on turnout and vote choice should be treated with caution, as we find no such effects. Rather, the actual virtue of VAAs in a complex online information environment lies in increasing knowledge about parties’ positions on issues—exactly the kind of information these tools were designed to provide.</abstract>
    <parentTitle language="eng">Public Opinion Quarterly</parentTitle>
    <identifier type="doi">10.1093/poq/nfaa037</identifier>
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    <licence>Metadaten / metadata</licence>
    <author>Simon Munzert</author>
    <submitter>Ayamba Kwoyila</submitter>
    <author>Pablo BarberÁ</author>
    <author>Andrew M. Guess</author>
    <author>JungHwan Yang</author>
    <thesisPublisher>Hertie School</thesisPublisher>
  </doc>
  <doc>
    <id>3977</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>14</issue>
    <volume>118</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2021-04-06</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The consequences of online partisan media</title>
    <abstract language="eng">What role do ideologically extreme media play in the polarization of society? Here we report results from a randomized longitudinal field experiment embedded in a nationally representative online panel survey (N = 1,037) in which participants were incentivized to change their browser default settings and social media following patterns, boosting the likelihood of encountering news with either a left-leaning (HuffPost) or right-leaning (Fox News) slant during the 2018 US midterm election campaign. Data on ≈ 19 million web visits by respondents indicate that resulting changes in news consumption persisted for at least 8 wk. Greater exposure to partisan news can cause immediate but short-lived increases in website visits and knowledge of recent events. After adjusting for multiple comparisons, however, we find little evidence of a direct impact on opinions or affect. Still, results from later survey waves suggest that both treatments produce a lasting and meaningful decrease in trust in the mainstream media up to 1 y later. Consistent with the minimal-effects tradition, direct consequences of online partisan media are limited, although our findings raise questions about the possibility of subtle, cumulative dynamics. The combination of experimentation and computational social science techniques illustrates a powerful approach for studying the long-term consequences of exposure to partisan news.</abstract>
    <parentTitle language="eng">Proceedings of the National Academy of Sciences</parentTitle>
    <identifier type="doi">10.1073/pnas.2013464118</identifier>
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    <licence>Metadaten / metadata</licence>
    <author>Andrew M. Guess</author>
    <editor>Christopher Andrew Bail</editor>
    <submitter>Ayamba Kwoyila</submitter>
    <author>Pablo Barberá</author>
    <author>Simon Munzert</author>
    <author>JungHwan Yang</author>
    <thesisPublisher>Hertie School</thesisPublisher>
  </doc>
  <doc>
    <id>4772</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>9</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-02-16</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Who’s cheating on your survey? A detection approach with digital trace data</title>
    <abstract language="eng">In this note, we provide direct evidence of cheating in online assessments of political knowledge. We combine survey responses with web tracking data of a German and a US online panel to assess whether people turn to external sources for answers. We observe item-level prevalence rates of cheating that range from 0 to 12 percent depending on question type and difficulty, and find that 23 percent of respondents engage in cheating at least once across waves. In the US panel, which employed a commitment pledge, we observe cheating behavior among less than 1 percent of respondents. We find robust respondent- and item-level characteristics associated with cheating. However, item-level instances of cheating are rare events; as such, they are difficult to predict and correct for without tracking data. Even so, our analyses comparing naive and cheating-corrected measures of political knowledge provide evidence that cheating does not substantially distort inferences.</abstract>
    <parentTitle language="eng">Political Science Research and Methods</parentTitle>
    <identifier type="doi">10.1017/psrm.2022.42</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Metadaten / metadata</licence>
    <author>Simon Munzert</author>
    <submitter>Alex Karras</submitter>
    <author>Sebastian Ramirez-Ruiz</author>
    <author>Pablo Barberá</author>
    <author>Andrew M. Guess</author>
    <author>JungHwan Yang</author>
    <collection role="Faculty" number=""/>
    <collection role="HertieResearch" number="">Data Science Lab</collection>
    <thesisPublisher>Hertie School</thesisPublisher>
  </doc>
  <doc>
    <id>5775</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue>2</issue>
    <volume>4</volume>
    <type>article</type>
    <publisherName>Oxford University Press (OUP)</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-03-21</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Citizen preferences for online hate speech regulation</title>
    <abstract language="eng">The shift of public discourse to online platforms has intensified the debate over content moderation by platforms and the regulation of online speech. Designing rules that are met with wide acceptance requires learning about public preferences. We present a visual vignette study using a sample (n=2,622) of German and US citizens that were exposed to 20,976 synthetic social media vignettes mimicking actual cases of hateful speech. We find people’s evaluations to be primarily shaped by message type and severity, and less by contextual factors. While focused measures like deleting hateful content are popular, more extreme sanctions like job loss find little support even in cases of extreme hate. Further evidence suggests in-group favoritism among political partisans. Experimental evidence shows that exposure to hateful speech reduces tolerance of unpopular opinions.</abstract>
    <parentTitle language="eng">PNAS Nexus</parentTitle>
    <identifier type="issn">2752-6542</identifier>
    <identifier type="doi">10.1093/pnasnexus/pgaf032</identifier>
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