1,893 research outputs found
Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign
Until recently, social media was seen to promote democratic discourse on
social and political issues. However, this powerful communication platform has
come under scrutiny for allowing hostile actors to exploit online discussions
in an attempt to manipulate public opinion. A case in point is the ongoing U.S.
Congress' investigation of Russian interference in the 2016 U.S. election
campaign, with Russia accused of using trolls (malicious accounts created to
manipulate) and bots to spread misinformation and politically biased
information. In this study, we explore the effects of this manipulation
campaign, taking a closer look at users who re-shared the posts produced on
Twitter by the Russian troll accounts publicly disclosed by U.S. Congress
investigation. We collected a dataset with over 43 million election-related
posts shared on Twitter between September 16 and October 21, 2016, by about 5.7
million distinct users. This dataset included accounts associated with the
identified Russian trolls. We use label propagation to infer the ideology of
all users based on the news sources they shared. This method enables us to
classify a large number of users as liberal or conservative with precision and
recall above 90%. Conservatives retweeted Russian trolls about 31 times more
often than liberals and produced 36x more tweets. Additionally, most retweets
of troll content originated from two Southern states: Tennessee and Texas.
Using state-of-the-art bot detection techniques, we estimated that about 4.9%
and 6.2% of liberal and conservative users respectively were bots. Text
analysis on the content shared by trolls reveals that they had a mostly
conservative, pro-Trump agenda. Although an ideologically broad swath of
Twitter users was exposed to Russian Trolls in the period leading up to the
2016 U.S. Presidential election, it was mainly conservatives who helped amplify
their message
Who let the trolls out? Towards understanding state-sponsored trolls
Recent evidence has emerged linking coordinated campaigns by state-sponsored actors to manipulate public opinion on the Web. Campaigns revolving around major political events are enacted via mission-focused ?trolls." While trolls are involved in spreading disinformation on social media, there is little understanding of how they operate, what type of content they disseminate, how their strategies evolve over time, and how they influence the Web's in- formation ecosystem. In this paper, we begin to address this gap by analyzing 10M posts by 5.5K Twitter and Reddit users identified as Russian and Iranian state-sponsored trolls. We compare the behavior of each group of state-sponsored trolls with a focus on how their strategies change over time, the different campaigns they embark on, and differences between the trolls operated by Russia and Iran. Among other things, we find: 1) that Russian trolls were pro-Trump while Iranian trolls were anti-Trump; 2) evidence that campaigns undertaken by such actors are influenced by real-world events; and 3) that the behavior of such actors is not consistent over time, hence detection is not straightforward. Using Hawkes Processes, we quantify the influence these accounts have on pushing URLs on four platforms: Twitter, Reddit, 4chan's Politically Incorrect board (/pol/), and Gab. In general, Russian trolls were more influential and efficient in pushing URLs to all the other platforms with the exception of /pol/ where Iranians were more influential. Finally, we release our source code to ensure the reproducibility of our results and to encourage other researchers to work on understanding other emerging kinds of state-sponsored troll accounts on Twitter.https://arxiv.org/pdf/1811.03130.pdfAccepted manuscrip
Comrades or Foes: Did the Russians Break the Law or New Ground for the First Amendment?
This Article discusses the recent decision by the United States Federal Government to indict more than a dozen Russian nationals for conspiracy to defraud the United States of America. The Government accused the Russians of staging protests, distributing false propaganda, and spreading political messages and ideologies online in an effort to affect the outcome of the 2016 Presidential Election. We argue that while the Defendants violated several other laws, the majority of the acts the Government classifies as a conspiracy to defraud the United States should not be considered criminal. Rather, these acts are protected political speech under the First Amendment of the United States Constitution because the Russians engaged in conduct that is crucial to political discourse in a Democracy and which the Founding Fathers intended to protect. Therefore, prosecution of the Russian Defendants on that basis should cease
Who Falls for Online Political Manipulation?
Social media, once hailed as a vehicle for democratization and the promotion
of positive social change across the globe, are under attack for becoming a
tool of political manipulation and spread of disinformation. A case in point is
the alleged use of trolls by Russia to spread malicious content in Western
elections. This paper examines the Russian interference campaign in the 2016 US
presidential election on Twitter. Our aim is twofold: first, we test whether
predicting users who spread trolls' content is feasible in order to gain
insight on how to contain their influence in the future; second, we identify
features that are most predictive of users who either intentionally or
unintentionally play a vital role in spreading this malicious content. We
collected a dataset with over 43 million elections-related posts shared on
Twitter between September 16 and November 9, 2016, by about 5.7 million users.
This dataset includes accounts associated with the Russian trolls identified by
the US Congress. Proposed models are able to very accurately identify users who
spread the trolls' content (average AUC score of 96%, using 10-fold
validation). We show that political ideology, bot likelihood scores, and some
activity-related account meta data are the most predictive features of whether
a user spreads trolls' content or not
A Historical and Contextual Analysis of Soviet and Russian Active Measures : How Russian Political Warfare Efforts in Foreign Presidential Elections Have Transformed in the Information Age
This thesis seeks to analyze the transformation of Russian active measures in targeted national elections since the Soviet era. Through a historical analysis of research on active measures and contextual analysis of active measures campaigns themselves, this thesis finds that Russian active measures techniques have not drastically changed since the Soviet era. Instead, as a result of technology, Russian active measures have utilized platforms of social media to become more targeted, continuous, and convert. Therefore, Russian active measures campaigns have been better able to successfully target specific audiences, arguably making these campaigns more effective
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