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Contrasting Public Opinion Dynamics and Emotional Response During Crisis

  • Conference paper
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Social Informatics (SocInfo 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10046))

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Abstract

We propose an approach for contrasting spatiotemporal dynamics of public opinions expressed toward targeted entities, also known as stance detection task, in Russia and Ukraine during crisis. Our analysis relies on a novel corpus constructed from posts on the VKontakte social network, centered on local public opinion of the ongoing Russian-Ukrainian crisis, along with newly annotated resources for predicting expressions of fine-grained emotions including joy, sadness, disgust, anger, surprise and fear. Akin to prior work on sentiment analysis we align traditional public opinion polls with aggregated automatic predictions of sentiments for contrastive geo-locations. We report interesting observations on emotional response and stance variations across geo-locations. Some of our findings contradict stereotypical misconceptions imposed by media, for example, we found posts from Ukraine that do not support Euromaidan but support Putin, and posts from Russia that are against Putin but in favor USA. Furthermore, we are the first to demonstrate contrastive stance variations over time across geo-locations using storyline visualization (Storyline visualization is available at http://www.cs.jhu.edu/~svitlana/) technique.

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Notes

  1. 1.

    Anonymized VK corpus is available upon request at http://www.cs.jhu.edu/~svitlana/.

  2. 2.

    Pre-trained models for emotion prediction and data annotated with 6 Ekman’s emotions in Russian and Ukrainian can be found at http://www.cs.jhu.edu/~svitlana/.

  3. 3.

    Social Network Analysis Reveals Full Scale of Kremlin’s Twitter Bot: https://globalvoices.org/2015/04/02/analyzing-kremlin-twitter-bots/.

  4. 4.

    Inside Putin’s Campaign Of Social Media Trolling And Faked Ukrainian Crimes: http://www.forbes.com/sites/paulroderickgregory/2014/05/11/inside-putins-campaign-of-social-media-trolling-and-faked-ukrainian-crimes/#238cfd72629d.

  5. 5.

    Ukraine conflict: Inside Russia’s ’Kremlin troll army’: http://www.bbc.com/news/world-europe-31962644.

  6. 6.

    VK demographics: http://www.slideshare.net/andrewik1/v-kontakte-demographics.

  7. 7.

    Minsk I: https://en.wikipedia.org/wiki/Minsk_Protocol.

  8. 8.

    Minsk II: https://en.wikipedia.org/wiki/Minsk_II.

  9. 9.

    We prefer Ekman’s emotion classification over others e.g., Plutchik’s, because we would like to compare the performance of our predictive models to other systems.

  10. 10.

    Morphological analyzer for Russian: https://pypi.python.org/pypi/pymorphy2.

  11. 11.

    Donetsk people’s republic: https://en.wikipedia.org/wiki/Luhansk_People’s_Republic.

  12. 12.

    Luhansk People’s Republic: https://en.wikipedia.org/wiki/Luhansk_People’s_Republic.

  13. 13.

    http://www.cbsnews.com/videos/cbs-news-trending-stories-for-november-5-2015/.

  14. 14.

    http://theweek.com/10things/580982/10-things-need-know-today-november-7-2015.

  15. 15.

    http://www.nytimes.com/2014/11/18/world/europe/eu-to-toughen-sanctions-on-ukraine-separatists-but-not-russia.html?_r=1.

  16. 16.

    http://www.cnbc.com/2014/11/17/german-economy-minister-rejects-tougher- sanctions-on-russia.html#.

  17. 17.

    http://www.gallup.com/poll/122840/gallup-daily-economic-indexes.aspx.

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Author information

Authors and Affiliations

  1. Pacific Northwest National Laboratory, Richland, Washington, USA

    Svitlana Volkova & Dustin Arendt

  2. Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Moscow, Russia

    Ilia Chetviorkin

  3. Center for Language and Speech Processing, Johns Hopkins University, Human Language Technology Center of Excellence, Baltimore, Maryland, USA

    Svitlana Volkova & Benjamin Van Durme

Authors
  1. Svitlana Volkova
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  2. Ilia Chetviorkin
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  3. Dustin Arendt
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  4. Benjamin Van Durme
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Correspondence to Svitlana Volkova .

Editor information

Editors and Affiliations

  1. University of Washington, Seattle, Washington, USA

    Emma Spiro

  2. Indiana University, Bloomington, Indiana, USA

    Yong-Yeol Ahn

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Volkova, S., Chetviorkin, I., Arendt, D., Van Durme, B. (2016). Contrasting Public Opinion Dynamics and Emotional Response During Crisis. In: Spiro, E., Ahn, YY. (eds) Social Informatics. SocInfo 2016. Lecture Notes in Computer Science(), vol 10046. Springer, Cham. https://doi.org/10.1007/978-3-319-47880-7_19

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