TY - GEN
T1 - Evaluating text visualization
T2 - 11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013
AU - Benjamin, Victor
AU - Chung, Wingyan
AU - Abbasi, Ahmed
AU - Chuang, Joshua
AU - Larson, Catherine A.
AU - Chen, Hsinchun
PY - 2013/9/9
Y1 - 2013/9/9
N2 - Analyzing authorship of online texts is an important analysis task in security-related areas such as cybercrime investigation and counter-terrorism, and in any field of endeavor in which authorship may be uncertain or obfuscated. This paper presents an automated approach for authorship analysis using machine learning methods, a robust stylometric feature set, and a series of visualizations designed to facilitate analysis at the feature, author, and message levels. A testbed consisting of 506,554 forum messages, in English and Arabic, from 14,901 authors was first constructed. A prototype portal system was then developed to support feasibility analysis of the approach. A preliminary evaluation to assess the efficacy of the text visualizations was conducted. The evaluation showed that task performance with the visualization functions was more accurate and more efficient than task performance without the visualizations.
AB - Analyzing authorship of online texts is an important analysis task in security-related areas such as cybercrime investigation and counter-terrorism, and in any field of endeavor in which authorship may be uncertain or obfuscated. This paper presents an automated approach for authorship analysis using machine learning methods, a robust stylometric feature set, and a series of visualizations designed to facilitate analysis at the feature, author, and message levels. A testbed consisting of 506,554 forum messages, in English and Arabic, from 14,901 authors was first constructed. A prototype portal system was then developed to support feasibility analysis of the approach. A preliminary evaluation to assess the efficacy of the text visualizations was conducted. The evaluation showed that task performance with the visualization functions was more accurate and more efficient than task performance without the visualizations.
KW - authorship analysis
KW - online forum
KW - terrorism
KW - text visualization
UR - http://www.scopus.com/inward/record.url?scp=84883320316&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883320316&partnerID=8YFLogxK
U2 - 10.1109/ISI.2013.6578778
DO - 10.1109/ISI.2013.6578778
M3 - Conference contribution
AN - SCOPUS:84883320316
SN - 9781467362115
T3 - IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics
SP - 16
EP - 20
BT - IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics
Y2 - 4 June 2013 through 7 June 2013
ER -