Exploring Twitter to analyze the public's reaction patterns to recently reported homicides in London

PLoS One. 2015 Mar 26;10(3):e0121848. doi: 10.1371/journal.pone.0121848. eCollection 2015.

Abstract

Crime is an ubiquitous part of society. The way people express their concerns about crimes has been of particular interest to the scientific community. Over time, the numbers and kinds of available communication channels have increased. Today, social media services, such Twitter, present a convenient way to express opinions and concerns about crimes. The main objective of this study is to explore people's perception of homicides, specifically, how the characteristics and proximity of the event affect the public's concern about it. The analysis explores Twitter messages that refer to homicides that occurred in London in 2012. In particular, the dependence of tweeting propensity on the proximity, in space and time, of a crime incident and of people being concerned about that particular incident are examined. Furthermore, the crime characteristics of the homicides are analysed using logistic regression analysis. The results show that the proximity of the Twitter users' estimated home locations to the homicides' locations impacts on whether the associated crime news is spread or not and how quickly. More than half of the homicide related tweets are sent within the first week and the majority of them are sent within a month of the incident's occurrence. Certain crime characteristics, including the presence of a knife, a young victim, a British victim, or a homicide committed by a gang are predictors of the crime-tweets posting frequency.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Crime
  • Homicide*
  • Humans
  • Likelihood Functions
  • London
  • Models, Theoretical
  • Public Opinion*
  • Social Media*
  • Spatial Analysis
  • Time Factors

Grants and funding

This research was funded by the Austrian Science Fund (FWF) through the Doctoral College GIScience at the University of Salzburg (DK W 1237-N23). Part of the research was also funded by the Salzburg University of Applied Sciences.