Stereotypical gender actions can be extracted from Web text

Online social networks and micro-blogging services are no longer limited to the followers of the latest technologies or teenagers, as might once have been expected. Such technology and services are becoming widely adopted by the mainstream population as an integral part of their daily lives (Fox et al., 2009). A very prominent example of such an application is Twitter, a micro-blogging service. Twitter lets its users post very short (at most 140-character) messages - which are called tweets - about what they have been doing or thinking, or what they want to share with their friends and other people. Everyday, tens of millions of tweets are posted by users worldwide. The proliferation of publicly available, user-generated content is a vast source of social data and is already shaping the field of computational social science (Lazer et al., 2009; Thelwall et al., 2010a). Another field which enjoys the abundance of Web-based text is knowledge extraction and automated ontology building. An example application is KNEXT ( Kn owledge Ex traction from T ext) - a system proposed for extracting "general world knowledge from miscellaneous texts, including fiction" (Schubert and Tong, 2003). Web-based text is increasingly used as a source for everyday knowledge (frequently referred as commonsense knowledge).