Hunting for Troll Comments in News Community Forums

Abstract

There are different definitions of what a troll is. Certainly, a troll can be somebody who teases people to make them angry, or somebody who offends people, or somebody who wants to dominate any single discussion, or somebody who tries to manipulate people's opinion (sometimes for money), etc. The last definition is the one that dominates the public discourse in Bulgaria and Eastern Europe, and this is our focus in this paper.In our work, we examine two types of opinion manipulation trolls: paid trolls that have been revealed from leaked "reputation management contracts" and "mentioned trolls" that have been called such by several different people. We show that these definitions are sensible: we build two classifiers that can distinguish a post by such a paid troll from one by a non-troll with 81-82% accuracy; the same classifier achieves 81-82% accuracy on so called mentioned troll vs. non-troll posts. 1 The independent Bulgarian media Bivol published a leaked contract described the following services in favor of the government:"Monthly posting online of 250 comments by virtual users with varied, typical and evolving profiles from different (non-recurring) IP addresses to inform, promote, balance or counteract. The intensity of the provided online presence will be adequately distributed and will correspond to the political situation in the country." See

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“…We also want to add more knowledge sources, e.g., as in the SUper Team system (Mihaylova et al, 2016), including veracity, sentiment, complexity, troll user features as inspired by (Mihaylov et al, 2015a;Mihaylov et al, 2015b;Mihaylov and Nakov, 2016a), and PMI-based goodness polarity lexicons as in the PMI-cool system .…”

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“…Spam is unlikely in Wikipedia discussions and extremely rare so far in Gazzetta comments. Mihaylov and Nakov (2016) identify comments posted by opinion manipulation trolls. Dinakar et al (2011) and Dadvar et al (2013) detect cyberbullying.…”

Predicting Factuality of Reporting and Bias of News Media Sources

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