Twitter Sentiment Analysis for Security-Related Information Gathering

Anna Jurek, Maurice D. Mulvenna, Yaxin Bi

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

6 Citations (Scopus)

Abstract

Analysing public sentiment about future events, such as demonstration or parades, may provide valuable information while estimating the level of disruption and disorder during these events. Social media, such as Twitter or Facebook, provides views and opinions of users related to any public topics. Consequently, sentiment analysis of social media content may be of interest to different public sector organisations, especially in the security and law enforcement sector. In this paper we present a lexicon-based approach to sentiment analysis of Twitter content. The algorithm performs normalisation of the sentiment in an effort to provide intensity of the sentiment rather than positive/negative label. Following this, we evaluate an evidence-based combining function that supports the classification process in cases when positive and negative words co-occur in a tweet. Finally, we illustrate a case study examining the relation between sentiment of twitter posts related to English Defence League and the level of disorder during the EDL related events.
Original languageEnglish
Title of host publicationProceedings: 2014 IEEE Joint Intelligence and Security Informatics Conference (JISIC 2014)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages48-55
Number of pages8
ISBN (Electronic)9781479963645
ISBN (Print)9781479963638
DOIs
Publication statusPublished - 2014
EventIEEE Joint Intelligence and Security Informatics Conference - , United Kingdom
Duration: 24 Sep 2014 → …

Conference

ConferenceIEEE Joint Intelligence and Security Informatics Conference
CountryUnited Kingdom
Period24/09/2014 → …

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