Evaluating text visualization for authorship analysis

Abstract

Methods and tools to conduct authorship analysis of web contents is of growing interest to researchers and practitioners in various security-focused disciplines, including cybersecurity, counter-terrorism, and other fields in which authorship of text may at times be uncertain or obfuscated. Here we demonstrate an automated approach for authorship analysis of web contents. Analysis is conducted through the use of machine learning methodologies, an expansive stylometric feature set, and a series of visualizations intended to help facilitate authorship analysis at the author, message, and feature levels. To operationalize this, we utilize a testbed containing 506,554 forum messages in English and Arabic, source from 14,901 authors that participated in an online web forum. A prototype portal system providing authorship comparisons and visualizations was then designed and constructed in order to support feasibility analysis and real world value of the automated authorship analysis approach. A preliminary user evaluation was performed to assess the efficacy of visualizations, with evaluation results demonstrating task performance accuracy and efficiency was improved through use of the portal.

Techniques to detect terrorists/extremists on the dark web: a review

“…As observed in Table 2, many studies have been performed on the dark web using content mining techniques only (Abbasi et al , 2008; Benjamin et al , 2013, 2014; Chen, 2008b, 2009; Chen et al , 2008c; Elovici et al , 2004; Endy et al , 2010; Fu et al , 2010; L'Huillier et al , 2010; Prentice et al , 2011; Scanlon, 2014; Simanjuntak et al , 2010; Yang et al , 2009). Some studies have used both structure and content mining techniques to perform feature selection, extraction or topical analysis (Bouchard et al , 2014; Chen, 2008a, b; Fu et al , 2010; Larson and Chen, 2009; Last et al , 2008; Patil et al , 2013; Reid et al , 2005; Zhang et al , 2010; Zhou et al , 2005).…”

Emotion extraction and entrainment in social media: The case of U.S. immigration and border security

“…Social media analytics (SMA) is a rich set of tools and technologies most recently applied to security informatics [2,3]. Traditional domains that SMA is used include business intelligence, online product review analysis, and security informatics [4][5][6].…”