Identifying partisan slant in news articles and twitter during political crises

Dmytro Karamshuk*, Tetyana Lokot, Oleksandr Pryymak, Nishanth Sastry

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

12 Citations (Scopus)
187 Downloads (Pure)

Abstract

In this paper, we are interested in understanding the interrelationships between mainstream and social media in forming public opinion during mass crises, specifically in regards to how events are framed in the mainstream news and on social networks and to how the language used in those frames may allow to infer political slant and partisanship. We study the lingual choices for political agenda setting in mainstream and social media by analyzing a dataset of more than 40M tweets and more than 4M news articles from the mass protests in Ukraine during 2013–2014—known as “Euromaidan”—and the post-Euromaidan conflict between Russian, pro-Russian and Ukrainian forces in eastern Ukraine and Crimea. We design a natural language processing algorithm to analyze at scale the linguistic markers which point to a particular political leaning in online media and show that political slant in news articles and Twitter posts can be inferred with a high level of accuracy. These findings allow us to better understand the dynamics of partisan opinion formation during mass crises and the interplay between mainstream and social media in such circumstances.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer‐Verlag Berlin Heidelberg
Pages257-272
Number of pages16
Volume10046 LNCS
ISBN (Print)9783319478791
DOIs
Publication statusPublished - 23 Oct 2016
Event8th International Conference on Social Informatics, SocInfo 2016 - Bellevue, United States
Duration: 11 Nov 201614 Nov 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10046 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference8th International Conference on Social Informatics, SocInfo 2016
Country/TerritoryUnited States
CityBellevue
Period11/11/201614/11/2016

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