Proximity and Networked News Public: Structural Topic Modeling of Global Twitter Conversations about the 2017 Quebec Mosque Shooting

Authors

  • K. Hazel Kwon Arizona State University - Walter Cronkite School of Journalism
  • Monica Chadha Arizona State University - Walter Cronkite School of Journalism
  • Feng Wang Arizona State University - School of Mathematical and Natural Sciences

Keywords:

mass shooting, anti-Muslim, proximity, networked framing, topic modeling, networked public, hate crime, Twitter, construal level theory

Abstract

The current study used structural topic modeling to investigate the ways in which news of the 2017 Quebec mosque shooting mobilized global public discourse on Twitter. The resulting globally generated Twitter conversations were divided into 9 relevant topics, the prevalence of which were examined based on geographic and informational proximity to the location of the incident. Tweets posted from locations geographically closer to the shooting location prevalently incorporated individual-oriented and conflict-focused storytelling. Conversely, tweets geographically farther from the incident prevalently featured macro-narratives that pointed to societal implications. This study also explored informational distance, which defines the ability to access to in-depth news sources. Results showed that there were topical differences between journalist/institutional tweets and laymen tweets. This study concludes that proximity influences global conversations related to hate crime news.

Author Biographies

K. Hazel Kwon, Arizona State University - Walter Cronkite School of Journalism

Assistant Professor 

Monica Chadha, Arizona State University - Walter Cronkite School of Journalism

Assistant Professor

Feng Wang, Arizona State University - School of Mathematical and Natural Sciences

Associate Professor

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Published

2019-06-14

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Section

Articles