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The Internet is frequently used as a medium for exchange of information and opinions, as well as propaganda dissemination. In this study the use of sentiment analysis methodologies is proposed for classification of Web forum opinions in multiple languages. The utility of stylistic and syntactic features is evaluated for sentiment classification of English(More)
One of the problems often associated with online anonymity is that it hinders social accountability, as substantiated by the high levels of cybercrime. Although identity cues are scarce in cyberspace, individuals often leave behind textual identity traces. In this study we proposed the use of stylometric analysis techniques to help identify individuals(More)
The speed, ubiquity, and potential anonymity of Internet media - email, Web sites, and Internet forums - make them ideal communication channels for militant groups and terrorist organizations. Analyzing Web content has therefore become increasingly important to the intelligence and security agencies that monitor these groups. Authorship analysis can assist(More)
Online reputation systems are intended to facilitate the propagation of word of mouth as a credibility scoring mechanism for improved trust in electronic 50 AbbASI, chEN, AND NuNAMAkEr marketplaces. however, they experience two problems attributable to anonymity abuse—easy identity changes and reputation manipulation. In this study, we propose the use of(More)
Content analysis of computer-mediated communication (CMC) is important for evaluating the effectiveness of electronic communication in various organizational settings. CMC text analysis relies on systems capable of providing suitable navigation and knowledge discovery functionalities. However, existing CMC systems focus on structural features, with little(More)
A major concern when incorporating large sets of diverse n-gram features for sentiment classification is the presence of noisy, irrelevant, and redundant attributes. These concerns can often make it difficult to harness the augmented discriminatory potential of extended feature sets. We propose a rule-based multivariate text feature selection method called(More)
Analysis of affective intensities in computer-mediated communication is important in order to allow a better understanding of online users' emotions and preferences. Despite considerable research on textual affect classification, it is unclear which features and techniques are most effective. In this study, we compared several feature representations for(More)
Affects play an important role in influencing people's perceptions and decision making. Affect analysis is useful for measuring the presence of hate, violence, and the resulting propaganda dissemination across extremist groups. In this study we performed affect analysis of U.S. and Middle Eastern extremist group forum postings. We constructed an affect(More)
Digital libraries (DLs) for online discourse contain large amounts of valuable information that is difficult to navigate and analyze. Visualization systems developed to facilitate improved CMC archive analysis and navigation primarily focus on interaction information, with little emphasis on textual content. In this paper we present a system that provides(More)