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<p>The Euromaidan Revolution in Ukraine in 2014 saw a series of violent events leading to the ousting of then-President Yanukovych. Opposition to the revolution spiraled into the annexation of Crimea by Russia and ongoing skirmishes in eastern and southern Ukraine. Akin to the Arab Spring in 2011 that illustrated the influence of new media in galvanizing disparate groups to revolt against state authorities, we show that the analysis of sentiments through social media messages relating to the Euromaidan movement in Ukraine from 2013 to 2014 can reveal evidence of nascent plots against Ukrainian state authorities. We systematically examined the exonyms in native languages used by the groups for and against the Euromaidan movement in reference to outsider groups during their mobilization in Ukraine, and conducted a series of statistical tests to analyze the significance of social media-derived sentiment metrics in predicting violence across different periods of political administration in Ukraine. Our analysis of the Euromaidan mobilization indicates that the application of algorithms coded to detect and measure prevalent dissent expressed in native lexicons through social media can be used to substantially improve the accuracy of geospatial forecasts of violent events.
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<br>Subjects: Euromaidan; Ukraine; social media; Twitter; exonyms; collective violence</div>
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<dl><dd>Kuah, Weiqi</dd>
<dd>Chew, Yee Hur William</dd></dl></div>
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