Abstract:
Authorship recognition from micro-blogs such as Twitter is a challenging task due to limitation of text length to 140 characters. However, identification of micro-blog au...Show MoreMetadata
Abstract:
Authorship recognition from micro-blogs such as Twitter is a challenging task due to limitation of text length to 140 characters. However, identification of micro-blog authors is crucial in many cyber-crime investigations as well as in forensic applications. So far, traditional linguistic profiles such as Bag-Of-Words (BOW) and style-based markers have been investigated for identification of micro-blog authorship. The social interactive data in micro-blogs remained understudied for this purpose. In this paper, we examined authorship recognition based on the social interactions of users in Twitter and present a comparative analysis with BOW and style-based features. We obtained 97% recognition rate on a database of 70 Twitter users, which validates the superiority of using social interactive data compared to traditional linguistic profiles.
Date of Conference: 05-08 October 2017
Date Added to IEEE Xplore: 30 November 2017
ISBN Information: