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Searching for signs of extremism on the web: an introduction to Sentiment-based Identification of Radical Authors
- Source :
- Behavioral Sciences of Terrorism and Political Aggression. 10:39-59
- Publication Year :
- 2017
- Publisher :
- Informa UK Limited, 2017.
-
Abstract
- As violent extremists continue to surface in online discussion forums, law enforcement agencies search for new ways of uncovering their digital indicators. Researchers have both described and hypothesized a number of ways to detect online traces of potential extremists, yet this area of inquiry remains in its infancy. This study proposes a new search method that, through the analysis of sentiment, identifies the most radical users within online forums. Although this method is applicable to web-forums of any type, the method was evaluated on four Islamic forums containing approximately 1 million posts of its 26,000 unique users. Several characteristics of each user’s postings were examined, including their posting behavior and the content of their posts. The content was analyzed using Parts-Of-Speech tagging, sentiment analysis, and a novel algorithm called ‘Sentiment-based Identification of Radical Authors’, which accounts for a user’s percentile score for average sentiment score, volume of negati...
- Subjects :
- 021110 strategic, defence & security studies
Online discussion
Sociology and Political Science
Social Psychology
business.industry
Computer science
Sentiment score
Internet privacy
Sentiment analysis
0211 other engineering and technologies
Law enforcement
02 engineering and technology
World Wide Web
Identification (information)
Percentile rank
Political Science and International Relations
Terrorism
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
business
Subjects
Details
- ISSN :
- 19434480 and 19434472
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Behavioral Sciences of Terrorism and Political Aggression
- Accession number :
- edsair.doi...........66fdcdb37b504b49630388680ff07349
- Full Text :
- https://doi.org/10.1080/19434472.2016.1276612