Denis Stukal

TL;DR: The authors provide an overview of the current state of the literature on the relationship between social media; political polarization; and political "disinformation", a term used to encompass a wide range of types of information about politics found online.

TL;DR: A methodology for detecting bots on Twitter using an ensemble of classifiers is developed and applied to study bot activity within political discussions in the Russian Twittersphere, finding suggestive evidence that one prominent activity that bots were involved in on Russian political Twitter is the spread of news stories and promotion of media who produce them.

TL;DR: A novel classification of strategies employed by autocrats to combat hostile activity on the web and in social media in particular is introduced and distinguishes both online from offline response and exerting control from engaging in opinion formation.

TL;DR: For instance, the authors argues that when it comes to economic affairs, a highly sensitive topic for modern autocrats, the government's ability to censor in economic affairs is limited. But when it come to economic issues, autocrats manipulate news through censorship.

TL;DR: A deep neural network classifier is developed that separates pro-regime, anti- Regime, and neutral Russian Twitter bots by their political orientation, and is illustrated by applying it to bots operating in Russian political Twitter from 2015 to 2017.