Optimizing Short Message Text Sentiment Analysis for Mobile Device Forensics

Oluwapelumi Aboluwarin, Panos Andriotis, Atsuhiro Takasu, Theo Tryfonas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)
285 Downloads (Pure)

Abstract

Mobile devices are now the dominant medium for communications. Humans express various emotions when communicating with others and these communications can be analyzed to deduce their emotional inclinations. Natural language processing techniques have been used to analyze sentiment in text. However, most research involving sentiment analysis in the short message domain (SMS and Twitter) do not account for the presence of non-dictionary words. This chapter investigates the problem of sentiment analysis in short messages and the analysis of emotional swings of an individual over time. This provides an additional layer of information for forensic analysts when investigating suspects. The maximum entropy algorithm is used to classify short messages as positive, negative or neutral. Non-dictionary words are normalized and the impact of normalization and other features on classification is evaluated; in fact, this approach enhances the classification F-score compared with previous work. A forensic tool with an intuitive user interface has been developed to support the extraction and visualization of sentiment information pertaining to persons of interest. In particular, the tool presents an improved approach for identifying mood swings based on short messages sent by subjects. The timeline view provided by the tool helps pinpoint periods of emotional instability that may require further investigation. Additionally, the Apache Solr system used for indexing ensures that a forensic analyst can retrieve the desired information rapidly and efficiently using faceted search queries.
Original languageEnglish
Title of host publicationAdvances in Digital Forensics XII
Subtitle of host publication12th IFIP WG 11.9 International Conference, New Delhi, January 4-6, 2016, Revised Selected Papers
EditorsGilbert Peterson, Sujeet Shenoi
PublisherSpringer International Publishing AG
Pages69-87
Number of pages19
Volume2
ISBN (Electronic)978-3-319-46279-0
ISBN (Print)978-3-319-46278-3
DOIs
Publication statusPublished - 20 Sep 2016
EventTwelfth IFIP WG 11.9 International Conference on Digital Forensics - New Delhi, India
Duration: 4 Jan 20166 Jan 2016

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer International Publishing
Volume484
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

ConferenceTwelfth IFIP WG 11.9 International Conference on Digital Forensics
CountryIndia
CityNew Delhi
Period4/01/166/01/16

Keywords

  • Sentiment analysis
  • text mining
  • SMS
  • Twitter
  • normalization

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