2020
DOI: 10.31219/osf.io/ch8gj
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News Sharing on Social Media: Mapping the Ideology of News Media, Politicians, and the Mass Public

Abstract: This article examines the news sharing behavior of politicians and ordinary users by mapping the ideological sharing space of political information on social media. As data, we use the near-universal currency of online political information exchange: URLs (i.e. web links). We introduce a methodological approach (and statistical software) that unifies the measurement of political ideology online, using social media sharing data to jointly estimate the ideology of: (1) politicians; (2) social media users, and (3… Show more

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Cited by 22 publications
(20 citation statements)
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References 60 publications
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“…We identified Twitter users who had retweeted MSNBC or Fox News posts, collected up to their last 3,200 tweets, and classified each user’s partisanship based on the content they shared from left- versus right-leaning websites ( 15 ) (strength of partisanship was measured as the absolute value of partisanship score). We removed users with more than 15,000 followers or for whom the partisanship estimator was unable to return a score and then constructed a politically balanced set of users to form the subject pool for our experiment.…”
Section: Methodsmentioning
confidence: 99%
“…We identified Twitter users who had retweeted MSNBC or Fox News posts, collected up to their last 3,200 tweets, and classified each user’s partisanship based on the content they shared from left- versus right-leaning websites ( 15 ) (strength of partisanship was measured as the absolute value of partisanship score). We removed users with more than 15,000 followers or for whom the partisanship estimator was unable to return a score and then constructed a politically balanced set of users to form the subject pool for our experiment.…”
Section: Methodsmentioning
confidence: 99%
“…We start from the observation that these metadata and watch histories are only proxies for the underlying concepts of interest: user i's utility for watching a specific video j, or U i (v j ). In line with existing work (Barberá 2013;Eady et al 2019), we use a random utility model to formalize U i (v j ) as a function of the user's ideal point α i and the content of the video a j . Formally,…”
Section: Theorymentioning
confidence: 99%
“…To serve as a comparison group, we used a list of 219 channels associated with "mainstream" media accounts described in a working paper by Eady et al (2019). Although it has not yet been published, the project aims to "define the population of US national online news sources" on YouTube (per Eady).…”
Section: Comparing the Youtube Right And Msm In Content Creation And ...mentioning
confidence: 99%