@article{ce7f3ce1a1634dcc9aae5f83cec06a2b,
title = "Detecting Bots on Russian Political Twitter",
abstract = "Automated and semiautomated Twitter accounts, bots, have recently gained significant public attention due to their potential interference in the political realm. In this study, we develop a methodology for detecting bots on Twitter using an ensemble of classifiers and apply it to study bot activity within political discussions in the Russian Twittersphere. We focus on the interval from February 2014 to December 2015, an especially consequential period in Russian politics. Among accounts actively Tweeting about Russian politics, we find that on the majority of days, the proportion of Tweets produced by bots exceeds 50%. We reveal bot characteristics that distinguish them from humans in this corpus, and find that the software platform used for Tweeting is among the best predictors of bots. Finally, we find 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.",
keywords = "Russia, Twitter, bot detection, ensemble methods, machine learning",
author = "Denis Stukal and Sergey Sanovich and Richard Bonneau and Tucker, {Joshua A.}",
note = "Funding Information: We are extremely grateful to Pablo Barber{\'a}, Neal Beck, Rita Kamalova, Sean Kates, Megan Metzger, Jonathan Nagler, Jennifer Pan, Duncan Penfold-Brown, Margaret Roberts, and Anastasiia Shukhova for their feedback and valuable suggestions. The data were collected by the New York University Social Media and Political Participation (SMaPP) laboratory (https://wp.nyu.edu/smapp/), of which Bonneau and Tucker are codirectors along with John T. Jost and Jonathan Nagler. The SMaPP laboratory is supported by the INSPIRE program of the National Science Foundation (Award SES-1248077), the New York University Global Institute for Advanced Study, the Moore-Sloan Data Science Environment, Dean Thomas Carew{\textquoteright}s Research Investment Fund at New York University, and the John S. and James L. Knight Foundation. We are also grateful to our volunteer coders from the Higher School of Economics (Moscow, Russia): Ivan Aleksandrov, Valeria Babayan, Maret Bochaeva, Daria Bushina, Viktoria Dimova, Yulia Gav-rilova, Anastasia Gergel, Tatyana Glushkova, Alexandra Goncharova, Egor Ilin, Christina Ilina, Aleksandra Izyumova, Artem Kolganov, Nikita Konyukhov, Yulia Korneeva, Maria Kuz, Alena Kuznetsova, Nikita Lata, Alina Lyutikova, Maria Makarova, Kamila Malikova, Elena Malysheva, Polina Malyutina, Ekaterina Mikhay-lova, Dmitry Muravyov, Mikhail Murzin, Pavel Myslov-skiy, Timur Naushirvanov, Maxim Novokreschenov, Veronika Pankina, Anastasia Parshina, Dmitrii Proda-nov, Anastasia Rodygina, Zlata Sergeeva, Rais Shaidullin, Maria Sidorova, Viktor Sinitsyn, Anna Skosyreva, Timur Slavgorodskiy-Kazanets, Anna Sokol, Elizaveta Sokov-nina, Georgy Tarasenko, Oksana Tiulpinova, Azizbek Tulaganov, Natalia Vasilenok, Anna Velikanova, Alena Volodkina, Alexey Volokhovich, Anna Zaychik, and Kirill Ziborov. Publisher Copyright: {\textcopyright} 2017, Mary Ann Liebert, Inc.",
year = "2017",
month = dec,
doi = "10.1089/big.2017.0038",
language = "English (US)",
volume = "5",
pages = "310--324",
journal = "Big Data",
issn = "2167-6461",
publisher = "Mary Ann Liebert Inc.",
number = "4",
}