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2012 | OriginalPaper | Buchkapitel

19. Women’s Forums on the Dark Web

verfasst von : Hsinchun Chen

Erschienen in: Dark Web

Verlag: Springer New York

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Abstract

With the recent advent of Web 2.0, more and more women participate in and exchange opinions through community-based social media on the Internet. Questions concerning gender differences in the context of online communication have been raised. In this study, we develop a feature-based text classification framework to examine the online gender differences between female and male posters on web forums by analyzing writing styles and topics of interests. We examine the performance of different feature sets in an experiment involving political opinions. The results of our experimental study on this Islamic women’s political forum show that the feature sets containing both content-free and content-specific features perform significantly better than those consisting of only content-free features. In addition, feature subset selection can improve the classification results significantly. Female and male participants were found to have significantly different topics of interest in our study.

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Metadaten
Titel
Women’s Forums on the Dark Web
verfasst von
Hsinchun Chen
Copyright-Jahr
2012
Verlag
Springer New York
Buch
Dark Web

Print ISBN: 978-1-4614-1556-5

Electronic ISBN: 978-1-4614-1557-2

Copyright-Jahr: 2012

DOI
https://doi.org/10.1007/978-1-4614-1557-2_19

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