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International Conference on Social Informatics

SocInfo 2017: Social Informatics pp 391–404Cite as

Combining Network and Language Indicators for Tracking Conflict Intensity

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10540))

Abstract

This work seeks to analyze the dynamics of social or political conflict as it develops over time, using a combination of network-based and language-based measures of conflict intensity derived from social media data. Specifically, we look at the random-walk based measure of graph polarization, text-based sentiment analysis, and the corresponding shift in word meaning and use by the opposing sides. We analyze the interplay of these views of conflict using the Ukraine-Russian Maidan crisis as a case study.

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Notes

  1. 1.

    http://vk.com.

  2. 2.

    https://networkx.github.io/.

  3. 3.

    https://github.com/Wobot/Sentimental.

  4. 4.

    https://github.com/text-machine-lab/sentimental.

  5. 5.

    https://en.wikipedia.org/wiki/Cosine_similarity.

  6. 6.

    https://radimrehurek.com/gensim/.

  7. 7.

    We tested the Metis algorithm on our own data and found it recorded 80% accuracy predicting community membership.

  8. 8.

    https://en.wikipedia.org/wiki/Force-directed_graph_drawing.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Massachusetts Lowell, Lowell, USA

    Anna Rumshisky, Peter Potash, Alexey Romanov, Saurabh Kulshreshtha & Alex Gribov

  2. Department of Russian, Dartmouth College, Hanover, USA

    Mikhail Gronas

  3. Higher School of Economics, Moscow, Russia

    Mikhail Dubov

Authors
  1. Anna Rumshisky
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  2. Mikhail Gronas
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  3. Peter Potash
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  4. Mikhail Dubov
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  5. Alexey Romanov
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  6. Saurabh Kulshreshtha
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  7. Alex Gribov
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Corresponding author

Correspondence to Anna Rumshisky .

Editor information

Editors and Affiliations

  1. Indiana University, Bloomington, Indiana, USA

    Giovanni Luca Ciampaglia

  2. University of Washington, Seattle, Washington, USA

    Afra Mashhadi

  3. University of Oxford, Oxford, United Kingdom

    Taha Yasseri

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Rumshisky, A. et al. (2017). Combining Network and Language Indicators for Tracking Conflict Intensity. In: Ciampaglia, G., Mashhadi, A., Yasseri, T. (eds) Social Informatics. SocInfo 2017. Lecture Notes in Computer Science(), vol 10540. Springer, Cham. https://doi.org/10.1007/978-3-319-67256-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-67256-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67255-7

  • Online ISBN: 978-3-319-67256-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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