1,720,985 research outputs found

    Replication Data for: "Using Social Media to Promote Academic Research: Identifying the Benefits of Twitter for Sharing Academic Work"

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    Data for "Using Social Media to Promote Academic Research: Identifying the Benefits of Twitter for Sharing Academic Work" include dataset of tweets and legend linking article ID numbers to names

    Replication Data for: When Common Identities Decrease Trust: An Experimental Study of Partisan Women

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    How does sharing a common gender identity affect the relationship between Democratic and Republican women? Social psychological work suggests that common ingroup identities unite competing factions. After closely examining the conditions upon which the Common Ingroup Identity Model depends, I argue that opposing partisans who share the superordinate identity of being a woman will not reduce their intergroup biases. Instead, I predict that raising the salience of their gender will increase cross-party biases. I support my hypotheses with a nationally representative survey of 3,000 adult women and two survey experiments, each with over 1000 adult women. These findings have direct implications for how women evaluate one another in contentious political settings and, more broadly, for our understanding of when we can and cannot rely upon common identities to bridge the partisan divide

    Replication Data for "The Effect of Network Structure on Preference Formation"

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    This study uses 5 datasets: - Demographics - Exposure - Learning and Opinion - Simulation 1 - Simulation

    Replication Data for: When Common Identities Decrease Trust: An Experimental Study of Partisan Women

    No full text
    How does sharing a common gender identity affect the relationship between Democratic and Republican women? Social psychological work suggests that common ingroup identities unite competing factions. After closely examining the conditions upon which the Common Ingroup Identity Model depends, I argue that opposing partisans who share the superordinate identity of being a woman will not reduce their intergroup biases. Instead, I predict that raising the salience of their gender will increase cross-party biases. I support my hypotheses with a nationally representative survey of 3,000 adult women and two survey experiments, each with over 1000 adult women. These findings have direct implications for how women evaluate one another in contentious political settings and, more broadly, for our understanding of when we can and cannot rely upon common identities to bridge the partisan divide

    Replication Data for "The Effect of Network Structure on Preference Formation"

    No full text
    This study uses 5 datasets: - Demographics - Exposure - Learning and Opinion - Simulation 1 - Simulation

    Replication Data for: Partisan-Motivated Evaluations of Sexual Misconduct and the Mitigating Role of the #MeToo Movement

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    When individuals evaluate something as serious as sexual misconduct allegations in politics, they are often motivated to defend their party—but outside forces can reduce these partisan biases. We bridge work from political psychology with studies of social movements to theorize how the #MeToo movement helps to mitigate partisan-motivated evaluations of sexual misconduct. With a two-wave survey experiment, we find that partisans are more likely to view out-party members guilty of sexual misconduct and that individuals less likely to reflect are particularly biased in their evaluations. We then turn to the #MeToo Movement and its potential to promote reflection. We show that support for #MeToo is associated with more even-handed evaluations of sexual misconduct in politics, particularly among those unlikely to reflect on their own. This study contributes to our broader understanding of how movements can induce reflection and moderate partisan-motivated reasoning among the mass public
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