Abstract
As an important type of social media, the political Web forum has become a major communication channel for people to discuss and debate political, cultural and social issues. Although the Internet has a male-dominated history, more and more women have started to share their concerns and express opinions through online discussion boards and Web forums. This paper presents an automated approach to gender difference analysis of political Web forums. The approach uses rich textual feature representation and machine learning techniques to examine the online gender differences between female and male participants on political Web forums by analyzing writing styles and topics of interest. The results of gender difference analysis performed on a large and long-standing international Islamic women's political forum are presented, showing that female and male participants have significantly different topics of interest.
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