Twitter Sentiment Analysis for Security-Related Information Gathering

Research output: Chapter in Book/Report/Conference proceedingChapter

4 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.
LanguageEnglish
Title of host publication2014 IEEE Joint Intelligence and Security Informatics Conference
Place of PublicationThe Hague, The Netherlands
Pages48-55
ISBN (Electronic)978-1-4799-6364-5
DOIs
Publication statusPublished - Sep 2014

Fingerprint

Law enforcement
Labels
Demonstrations

Cite this

Jurek, A., Bi, Y., & Mulvenna, M. (2014). Twitter Sentiment Analysis for Security-Related Information Gathering. In 2014 IEEE Joint Intelligence and Security Informatics Conference (pp. 48-55). The Hague, The Netherlands. https://doi.org/10.1109/JISIC.2014.17
Jurek, Anna ; Bi, Yaxin ; Mulvenna, Maurice. / Twitter Sentiment Analysis for Security-Related Information Gathering. 2014 IEEE Joint Intelligence and Security Informatics Conference. The Hague, The Netherlands, 2014. pp. 48-55
@inbook{84a56c4597b14bfb9c2e18ffdfa7dc85,
title = "Twitter Sentiment Analysis for Security-Related Information Gathering",
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.",
author = "Anna Jurek and Yaxin Bi and Maurice Mulvenna",
year = "2014",
month = "9",
doi = "10.1109/JISIC.2014.17",
language = "English",
pages = "48--55",
booktitle = "2014 IEEE Joint Intelligence and Security Informatics Conference",

}

Jurek, A, Bi, Y & Mulvenna, M 2014, Twitter Sentiment Analysis for Security-Related Information Gathering. in 2014 IEEE Joint Intelligence and Security Informatics Conference. The Hague, The Netherlands, pp. 48-55. https://doi.org/10.1109/JISIC.2014.17

Twitter Sentiment Analysis for Security-Related Information Gathering. / Jurek, Anna; Bi, Yaxin; Mulvenna, Maurice.

2014 IEEE Joint Intelligence and Security Informatics Conference. The Hague, The Netherlands, 2014. p. 48-55.

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - Twitter Sentiment Analysis for Security-Related Information Gathering

AU - Jurek, Anna

AU - Bi, Yaxin

AU - Mulvenna, Maurice

PY - 2014/9

Y1 - 2014/9

N2 - 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.

AB - 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.

U2 - 10.1109/JISIC.2014.17

DO - 10.1109/JISIC.2014.17

M3 - Chapter

SP - 48

EP - 55

BT - 2014 IEEE Joint Intelligence and Security Informatics Conference

CY - The Hague, The Netherlands

ER -

Jurek A, Bi Y, Mulvenna M. Twitter Sentiment Analysis for Security-Related Information Gathering. In 2014 IEEE Joint Intelligence and Security Informatics Conference. The Hague, The Netherlands. 2014. p. 48-55 https://doi.org/10.1109/JISIC.2014.17