Dr Panos Andriotis Panagiotis.Andriotis@uwe.ac.uk
Senior Lecturer in Computer Forensics and Security
Smartphone message sentiment analysis
Andriotis, Panagiotis; Takasu, Atsuhiro; Tryfonas, Theo
Authors
Atsuhiro Takasu
Theo Tryfonas
Contributors
Gilbert Peterson
Editor
Sujeet Shenoi
Editor
Abstract
Humans tend to use specific words to express their emotional states in written and oral communications. Scientists in the area of text mining and natural language processing have studied sentiment fingerprints residing in text to extract the emotional polarity of customers for a product or to evaluate the popularity of politicians. Recent research focused on micro-blogging has found notable similarities between Twitter feeds and SMS (short message service) text messages. This paper investigates the common characteristics of both formats for sentiment analysis purposes and verifies the correctness of the similarity assumption. A lexicon-based approach is used to extract and compute the sentiment scores of SMS messages found on smartphones. The data is presented along a timeline that depicts a sender’s emotional fingerprint. This form of analysis and visualization can enrich a forensic investigation by conveying potential psychological patterns from text messages.
Citation
Andriotis, P., Takasu, A., & Tryfonas, T. (2014). Smartphone message sentiment analysis. In G. Peterson, & S. Shenoi (Eds.), Advances in Digital Forensics X (253-265). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-44952-3_17
Publication Date | Jan 1, 2014 |
---|---|
Print ISSN | 1868-4238 |
Peer Reviewed | Peer Reviewed |
Volume | 433 |
Pages | 253-265 |
Book Title | Advances in Digital Forensics X |
ISBN | 9783662449516 |
DOI | https://doi.org/10.1007/978-3-662-44952-3_17 |
Keywords | SMS messages, Twitter feeds, emotion, timeline |
Public URL | https://uwe-repository.worktribe.com/output/822819 |
Publisher URL | http://dx.doi.org/10.1007/978-3-662-44952-3_17 |
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