1.
Policing Engagement via Social
Media
Date: November 2014, SocInfo
Author: Miriam Fernandez, Amparo Elizabeth Cano, Harith Alani

2.
Context
• Policing organisations use social media to
spread the word on crime, severe weather,
missing people, …
• Many forces have staff dedicated to this
purpose and to improve the spreading of key
messages to wider social media communities
• Research shows that exchanges between
police and citizens are infrequent

3.
Goal
• Understand what attracts citizen’s to social
media policing content
– What are the characteristics of the content that
generate higher attention levels
• Writing style
• Time of posting
• Topics
– Help police forces to identify actions and
recommendations to increase public engagement

4.
Approach
• @Dorsetpolice Twitter account
– 3,200 posts [2011-12-23 / 2014-06-12]
• Announcements, appeals, crime reports, etc.
• Retweet as engagement indicator
– 2,270 (86%) seed vs. 430 non-seed posts
• Seed post = received at least one retweet
• Balance dataset for the analysis
• ML & Semantic techniques to analyse engagement

5.
ML Analysis
• Content Analysis [Rowe & Alani 2014]
– Top discriminative features of retweeted vs. non
retweeted posts
– Top discriminative features of highly retweeted
posts
• Tweets that generate higher attention
– Are longer
– Have positive sentiment
– Mention other users
– Are posted between
8:00 a.m 16:00 p.m
[Rowe & Alani 2014]. Mining and comparing engagement dynamics across multiple
social media platforms. WebScience 2014

6.
Semantic Analysis
• Annotate tweets with entities & concepts using
TextRazor
– DBPedia & Freebase as knowledge bases
• Seed posts talk about
– weather, roads and infrastructures & mention locations
• Non seed posts talk about
– crimes such as burglary, assault or driving under the
influence of alcohol.

7.
Conclusions
• Use a combination of ML and semantic
techniques to understand the most
discriminative language, time features and
topics of those tweets generating higher
attention levels towards policing content
• Preliminary study
– One social media platform (Twitter)
– One police force(@dorsetpolice)
– One engagement indicator (retweets)

8.
Questions?