Evaluating text visualization: An experiment in authorship analysis

Victor Benjamin; Wingyan Chung; Ahmed Abbasi; Joshua Chuang; Catherine A. Larson; Hsinchun Chen

doi:10.1109/ISI.2013.6578778

Evaluating text visualization: An experiment in authorship analysis

Victor Benjamin, Wingyan Chung, Ahmed Abbasi, Joshua Chuang, Catherine A. Larson, Hsinchun Chen

Management Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics
Subtitle of host publication	Big Data, Emergent Threats, and Decision-Making in Security Informatics
Pages	16-20
Number of pages	5
DOIs	https://doi.org/10.1109/ISI.2013.6578778
State	Published - Sep 9 2013
Event	11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 - Seattle, WA, United States Duration: Jun 4 2013 → Jun 7 2013

Publication series

Name	IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics

Other

Other	11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013
Country/Territory	United States
City	Seattle, WA
Period	6/4/13 → 6/7/13

Keywords

authorship analysis
online forum
terrorism
text visualization

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

Access to Document

10.1109/ISI.2013.6578778

Cite this

Benjamin, V., Chung, W., Abbasi, A., Chuang, J., Larson, C. A., & Chen, H. (2013). Evaluating text visualization: An experiment in authorship analysis. In IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics (pp. 16-20). [6578778] (IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics). https://doi.org/10.1109/ISI.2013.6578778

Evaluating text visualization : An experiment in authorship analysis. / Benjamin, Victor; Chung, Wingyan; Abbasi, Ahmed; Chuang, Joshua; Larson, Catherine A.; Chen, Hsinchun.

IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. p. 16-20 6578778 (IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Benjamin, V, Chung, W, Abbasi, A, Chuang, J, Larson, CA & Chen, H 2013, Evaluating text visualization: An experiment in authorship analysis. in IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics., 6578778, IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics, pp. 16-20, 11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013, Seattle, WA, United States, 6/4/13. https://doi.org/10.1109/ISI.2013.6578778

Benjamin V, Chung W, Abbasi A, Chuang J, Larson CA, Chen H. Evaluating text visualization: An experiment in authorship analysis. In IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. p. 16-20. 6578778. (IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics). https://doi.org/10.1109/ISI.2013.6578778

Benjamin, Victor ; Chung, Wingyan ; Abbasi, Ahmed ; Chuang, Joshua ; Larson, Catherine A. ; Chen, Hsinchun. / Evaluating text visualization : An experiment in authorship analysis. IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. pp. 16-20 (IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics).

@inproceedings{73b58be658a144b08398be457c09b15d,

title = "Evaluating text visualization: An experiment in authorship analysis",

abstract = "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.",

keywords = "authorship analysis, online forum, terrorism, text visualization",

author = "Victor Benjamin and Wingyan Chung and Ahmed Abbasi and Joshua Chuang and Larson, {Catherine A.} and Hsinchun Chen",

year = "2013",

month = sep,

day = "9",

doi = "10.1109/ISI.2013.6578778",

language = "English (US)",

isbn = "9781467362115",

series = "IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics",

pages = "16--20",

booktitle = "IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics",

note = "11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 ; Conference date: 04-06-2013 Through 07-06-2013",

}

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 -

Evaluating text visualization: An experiment in authorship analysis

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this