11 research outputs found
Socio-Linguistic Characteristics of Coordinated Inauthentic Accounts
Online manipulation is a pressing concern for democracies, but the actions
and strategies of coordinated inauthentic accounts, which have been used to
interfere in elections, are not well understood. We analyze a five
million-tweet multilingual dataset related to the 2017 French presidential
election, when a major information campaign led by Russia called "#MacronLeaks"
took place. We utilize heuristics to identify coordinated inauthentic accounts
and detect attitudes, concerns and emotions within their tweets, collectively
known as socio-linguistic characteristics. We find that coordinated accounts
retweet other coordinated accounts far more than expected by chance, while
being exceptionally active just before the second round of voting.
Concurrently, socio-linguistic characteristics reveal that coordinated accounts
share tweets promoting a candidate at three times the rate of non-coordinated
accounts. Coordinated account tactics also varied in time to reflect news
events and rounds of voting. Our analysis highlights the utility of
socio-linguistic characteristics to inform researchers about tactics of
coordinated accounts and how these may feed into online social manipulation.Comment: 12 pages, 9 figure
Trumpism and the American Politics of Insecurity
No description supplie
MOTIV: Visual Exploration of Moral Framing in Social Media
We present a visual computing framework for analyzing moral rhetoric on
social media around controversial topics. Using Moral Foundation Theory, we
propose a methodology for deconstructing and visualizing the \textit{when},
\textit{where}, and \textit{who} behind each of these moral dimensions as
expressed in microblog data. We characterize the design of this framework,
developed in collaboration with experts from language processing,
communications, and causal inference. Our approach integrates microblog data
with multiple sources of geospatial and temporal data, and leverages
unsupervised machine learning (generalized additive models) to support
collaborative hypothesis discovery and testing. We implement this approach in a
system named MOTIV. We illustrate this approach on two problems, one related to
Stay-at-home policies during the COVID-19 pandemic, and the other related to
the Black Lives Matter movement. Through detailed case studies and discussions
with collaborators, we identify several insights discovered regarding the
different drivers of moral sentiment in social media. Our results indicate that
this visual approach supports rapid, collaborative hypothesis testing, and can
help give insights into the underlying moral values behind controversial
political issues.
Supplemental Material:
https://osf.io/ygkzn/?view_only=6310c0886938415391d977b8aae8b74
Socio-Linguistic Characteristics of Coordinated Inauthentic Accounts
Online manipulation is a pressing concern for democracies, but the actions and strategies of coordinated inauthentic accounts, which have been used to interfere in elections, are not well understood. We analyze a five million-tweet multilingual dataset related to the 2017 French presidential election, when a major information campaign led by Russia called "#MacronLeaks" took place. We utilize heuristics to identify coordinated inauthentic accounts and detect attitudes, concerns and emotions within their tweets, collectively known as socio-linguistic characteristics. We find that coordinated accounts retweet other coordinated accounts far more than expected by chance, while being exceptionally active just before the second round of voting. Concurrently, socio-linguistic characteristics reveal that coordinated accounts share tweets promoting a candidate at three times the rate of non-coordinated accounts. Coordinated account tactics also varied in time to reflect news events and rounds of voting. Our analysis highlights the utility of socio-linguistic characteristics to inform researchers about tactics of coordinated accounts and how these may feed into online social manipulation