  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 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.
