DocumentCode :
1827549
Title :
Content feature enrichment for analyzing trust relationships in web forums
Author :
Piorkowski, John ; Lina Zhou
Author_Institution :
Univ. of Maryland Baltimore County, Baltimore, MD, USA
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
1486
Lastpage :
1487
Abstract :
As criminals and terrorist employ social media platforms for planning and executing nefarious activities, understanding the degree of trustworthiness in interactions among actors becomes crucial for detecting their activities. Measuring trust in these environments can benefit analysts who are monitoring web forums to detect criminal or terrorist activities. Previous research proposed a trust model that could enable automatic trust discovery using speech act theory. This paper introduces a new classification method that enriches traditional techniques with contextual information. We conducted experiments to compare the proposed method with traditional approaches. The results show that the proposed method outperforms other alternative methods.
Keywords :
computer crime; pattern classification; planning; social networking (online); terrorism; trusted computing; Web forum monitoring; automatic trust discovery; classification method; content feature enrichment; criminal activity detection; nefarious activity planning; social media platforms; speech act theory; terrorist activity detection; trust measurement; trust relationship analysis; Conferences; Decision trees; Feature extraction; Social network services; Speech; Support vector machines; Terrorism;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON
Type :
conf
Filename :
6785916
Link To Document :
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