A Machine Learning Analysis of Twitter Sentiment to the Sandy Hook Shootings

Nan Wang, Blesson Varghese, Peter Donnelly

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)
283 Downloads (Pure)

Abstract

Gun related violence is a complex issue and accounts for a large proportion of violent incidents. In the research reported in this paper, we set out to investigate the pro-gun and anti-gun sentiments expressed on a social media platform, namely Twitter, in response to the 2012 Sandy Hook Elementary School shooting in Connecticut, USA. Machine learning techniques are applied to classify a data corpus of over 700,000 tweets. The sentiments are captured using a public sentiment score that considers the volume of tweets as well as population. A web-based interactive tool is developed to visualise the sentiments and is available at this http://www.gunsontwitter.com. The key findings from this research are: (i) There are elevated rates of both pro-gun and anti-gun sentiments on the day of the shooting. Surprisingly, the pro-gun sentiment remains high for a number of days following the event but the anti-gun sentiment quickly falls to pre-event levels. (ii) There is a different public response from each state, with the highest pro-gun sentiment not coming from those with highest gun ownership levels but rather from California, Texas and New York.
Original languageEnglish
Title of host publication2016 IEEE 12th International Conference on e-Science (e-Science)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)978-1-5090-4273-9
ISBN (Print)978-1-5090-4274-6
DOIs
Publication statusPublished - 06 Mar 2017
Event2016 IEEE 12th International Conference on eScience - Baltimore, United States
Duration: 23 Oct 201627 Oct 2016
http://escience-2016.idies.jhu.edu/

Conference

Conference2016 IEEE 12th International Conference on eScience
CountryUnited States
CityBaltimore
Period23/10/201627/10/2016
Internet address

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