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                            Library & Multimedia
 Viewing anti-immigrant hate online: An application of routine activity and Social Structure-Social Learning Theory
NCJ Number
              304058
Journal

*Computers in Human Behavior* Volume: 124 Dated: 2021
Author(s)
          M. Costello;
                        et al
Date Published

2021
Annotation
              Given the recent rise in online hate that targets immigrants, this study examined factors that bring individuals into virtual contact with such material.
Abstract
              The increasingly prominent role of the Internet in the lives of Americans has resulted in more people coming into contact with various types of online content, including online hate material. One of the most common forms of online hate targets immigrants, seeking to portray immigrants as threats to personal, national, economic, and cultural security. Using recently collected online survey data of American youth and young adults, this study drew on insights from Routine Activity Theory and Social Structure-Social Learning Theory to understand exposure to anti-immigrant online hate material. Specifically, the study considered how online routines, location in social structure, and social identity are associated with exposure. Results indicate that engaging in behaviors that can increase proximity to motivated offenders increases the likelihood of being exposed to anti-immigrant hate, as does engaging in online behaviors that bolster one's target suitability. In addition. individuals who view Americanism as fundamental to their social identity are more likely to encounter anti-immigrant hate material on the Internet, as are those who are more dissatisfied with the current direction of the country. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2014-ZA-BX-0014


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        Radicalization on the Internet: Virtual Extremism in the US from 2012-2017
    
  
  
Date Published: January 1, 2021
    
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Related Datasets
        
                      https://doi.org/10.3886/ICPSR37679.v1
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