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dc.contributor.advisorEbner, Rachelen_US
dc.contributor.authorMotechin, Miriam
dc.date.accessioned2019-07-10T14:29:47Z
dc.date.available2019-07-10T14:29:47Z
dc.date.issued2019-05-07
dc.identifier.citationMotechin, Miriam. The Impact of Avatar Customization in Violent Video Games on Aggressive Outcomes Presented to the S. Daniel Abrahams Honors Program in Partial Fulfillment of the Requirements for Completion of the Program Stern College for Women Yeshiva University May 7, 2019.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12202/4498
dc.descriptionThe file is restricted for YU community access only.en_US
dc.description.abstractThis research proposal hypothesizes that character customization in violent video games will lead to increased levels of aggression in the players due to a stronger cognitive identification with the model. 100 college students in New York City will participate, using Grand Theft Auto Online as the video game and a sentence completion task in order to measure levels of aggression. Past research on effects of violent video games as well as a theoretical framework for this study are discussed. Possible limitations and areas for future research are included.en_US
dc.description.sponsorshipS Daniel Abraham Honors Program of Stern College for Womenen_US
dc.language.isoen_USen_US
dc.publisherStern College for Women Yeshiva University.en_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectAvatar customizationen_US
dc.subjectsenior honors thesisen_US
dc.subjectviolent video gamesen_US
dc.subjectaggressive outcomesen_US
dc.titleThe Impact of Avatar Customization in Violent Video Games on Aggressive Outcomes.en_US
dc.typeThesisen_US


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  • Honors Student Theses [208]
    Senior honors theses sponsored by the S. Daniel Abraham Honors Program of Stern College for Women

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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States