Partisanship, Propaganda and Post-Truth Politics: Quantifying Impact in Online Debate



Published Aug 28, 2019


The recent past has highlighted the influential role of social networks and online media in shaping public debate on current affairs
and political issues. This paper is focused on studying the role of politically-motivated actors and their strategies for influencing
and manipulating public opinion online: partisan media, state-backed propaganda, and post-truth politics. In particular, we present
quantitative research on the presence and impact of these three “Ps” in online Twitter debates in two contexts: (i) the run up to
the UK EU membership referendum (“Brexit”); and (ii) the information operations of Russia-backed online troll accounts. We first
compare the impact of highly partisan versus mainstream media during the Brexit referendum, specifically comparing tweets by half
a million “leave” and “remain” supporters. Next, online propaganda strategies are examined, specifically left- and right-wing troll
accounts. Lastly, we study the impact of misleading claims made by the political leaders of the leave and remain campaigns. This
is then compared to the impact of the Russia-backed partisan media and propaganda accounts during the referendum. In particular,
just two of the many misleading claims made by politicians during the referendum were found to be cited in 4.6 times more tweets
than the 7,103 tweets related to Russia Today and Sputnik and in 10.2 times more tweets than the 3,200 Brexit-related tweets by
the Russian troll accounts.
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[1] H. Allcott and M. Gentzkow. Social media and fake news
in the 2016 election. Journal of Economic Perspectives,
31(2):211–36, 2017.

[2] P. Barberá and G. Rivero. Understanding the political rep-
resentativeness of Twitter users. Social Science Computer
Review, 33(6):712–729, 2015.

[3] M. T. Bastos and D. Mercea. The Brexit botnet and user-
generated hyperpartisan news. Social Science Computer
Review, 2017.

[4] R. Faris, H. Roberts, B. Etling, N. Bourassa, E. Zuckerman,
and Y. Benkler. Partisanship, propaganda, and disinforma-
tion: Online media and the 2016 US presidential election.
Berkman Klein Center for Internet & Society Research Pa-
per, 2017.

[5] E. Ferrara. Disinformation and social bot operations in the
run up to the 2017 French presidential election. First Mon-
day, 22(8), 2017.

[6] C. Hare and K. T. Poole. The polarization of contemporary
american politics. Polity, 46(3):411–429, 2014.

[7] K. Higgins. Post-truth: a guide for the perplexed. Nature
News, 540(7631):9, 2016.

[8] P. N. Howard and B. Kollanyi. Bots, #strongerin, and
#brexit: Computational propaganda during the UK-EU ref-
erendum. Technical report, Working Paper 2016.1. Oxford,
UK: Project on Computational Propaganda., 2016.

[9] M. Kaminska, B. Kollanyi, and P. N. Howard. Junk news
and bots during the 2017 UK general election: What are
UK voters sharing over Twitter? Technical report, Data
Memo 2017.5. Oxford, UK: Project on Computational Pro-
paganda., 2017.

[10] T. Lansdall-Welfare, F. Dzogang, and N. Cristianini.
Change-point analysis of the public mood in UK Twitter
during the Brexit referendum. In Data Mining Workshops
(ICDMW), 2016 IEEE 16th International Conference on,
pages 434–439. IEEE, 2016.

[11] S. Lewandowsky, U. K. Ecker, and J. Cook. Beyond misin-
formation: Understanding and coping with the “post-truth”
era. Journal of Applied Research in Memory and Cogni-
tion, 6(4):353–369, 2017.

[12] D. Linvill and P. Warren. Troll factories: The internet re-
search agency and state-sponsored agenda building. pwar-
ren. people. clemson. edu/Linvill Warren TrollFactory.
pdf, 2018.

[13] L. Mangold. Should I stay or should I go: Clash of opinions
in the Brexit Twitter debate. Computing, 1(4.1), 2016.

[14] M. Moore and G. Ramsay. UK media coverage of the 2016
EU referendum campaign. King’s College London, 2017.

[15] V. Narayanan, P. N. Howard, B. Kollanyi, and M. Elswah.
Russian involvement and junk news during Brexit. Tech-
nical report, Data Memo 2017.10. Oxford, UK: Project on
Computational Propaganda., 2017.

[16] N. Persily. The 2016 us election: Can democracy survive
the internet? Journal of democracy, 28(2):63–76, 2017.

[17] D. Preoţiuc-Pietro, Y. Liu, D. Hopkins, and L. Ungar. Be-
yond binary labels: political ideology prediction of Twit-
ter users. In Proceedings of the 55th Annual Meeting of
the Association for Computational Linguistics (Volume 1:
Long Papers), volume 1, pages 729–740, 2017.

[18] C. Shao, G. L. Ciampaglia, O. Varol, K.-C. Yang, A. Flam-
mini, and F. Menczer. The spread of low-credibility con-
tent by social bots. Nature communications, 9(1):4787,

[19] C. Silverman. Lies, damn lies and viral content. Technical
report, Tow Center for Digital Journalism, 2015.

[20] H. T. Skjeseth. All the president’s lies: Media coverage
of lies in the US and france. Technical report, Reuters In-
stitute for the Study of Journalism, University of Oxford,

[21] T. Venturini. From fake to junk news, the data politics of
online virality. In D. Bigo, E. Isin, and E. Ruppert, ed-
itors, Data Politics: Worlds, Subjects, Rights. Routledge,
London, 2019.

[22] S. Vosoughi, D. Roy, and S. Aral. The spread of true and
false news online. Science, 359(6380):1146–1151, 2018.