Detecting Sockpuppets in Social Media with Plagiarism Detection Algorithms
Fredrik Albrektsson · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2017
As new forms of propaganda and information control spread across the internet, the need for novel ways of identifying them increases as well. One increasingly popular method of spreading false messages on microblogs like Twitter is to disseminate them from seemingly ordinary, but centrally controlled and coordinated user accounts – sockpuppets. In this paper we examine a number of potential methods for identifying these by way of applying plagiarism detection algorithms for text, and evaluate their performance against this type of threat. We identify one type of algorithm in particular – that using vector space modeling of text – as particularly useful in this regard.