Mihaylov, Todor ; Nakov, Preslav (2016)
Hunting for Troll Comments in News Community Forums.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2016 |
| Autor(en): | Mihaylov, Todor ; Nakov, Preslav |
| Art des Eintrags: | Bibliographie |
| Titel: | Hunting for Troll Comments in News Community Forums |
| Sprache: | Deutsch |
| Publikationsjahr: | August 2016 |
| Verlag: | Association for Computational Linguistics |
| Buchtitel: | Proceedings of the 54rd Annual Meeting of the Association for Computational Linguistics |
| URL / URN: | http://www.aclweb.org/anthology/K15-1032 |
| Zugehörige Links: | |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | AIPHES_area_a2 |
| ID-Nummer: | TUD-CS-2016-0158 |
| Fachbereich(e)/-gebiet(e): | DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen |
| Hinterlegungsdatum: | 30 Dez 2016 17:45 |
| Letzte Änderung: | 28 Sep 2018 15:14 |
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