Communication power struggles on social media: A case study of the 2011–12 Russian protests

Spaiser, Viktoria; Chadefaux, Thomas; Donnay, Karsten; Russmann, Fabian; Helbing, Dirk

doi:10.1080/19331681.2017.1308288

Cited by 60 publications

(37 citation statements)

References 48 publications

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“…Yet the challenges are also formidable. Most of what is written on social media is either irrelevant for the purposes of conflict forecasting -tweets, for example, are massively polluted by spam -or is deliberately false information planted by the government for purposes of manipulation (Spaiser et al [52]).…”

Section: Econometric Approachesmentioning

confidence: 99%

Conflict forecasting and its limits

Chadefaux

2017

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Research on international conflict has mostly focused on explaining events such as the onset or termination of wars, rather than on trying to predict them. Recently, however, forecasts of political phenomena have received growing attention. Predictions of violent events, in particular, have been increasingly accurate using various methods ranging from expert knowledge to quantitative methods and formal modeling. Yet, we know little about the limits of these approaches, even though information about these limits has critical implications for both future research and policy-making. In particular, are our predictive inaccuracies due to limitations of our models, data, or assumptions, in which case improvements should occur incrementally. Or are there aspects of conflicts that will always remain fundamentally unpredictable? After reviewing some of the current approaches to forecasting conflict, I suggest avenues of research that could disentangle the causes of our current predictive failures.

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Section: Econometric Approachesmentioning

confidence: 99%

Conflict forecasting and its limits

Chadefaux

2017

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“…al. examined a wave of mass protests surrounding the Duma and presidential elections happening in Russia between 2011 and 2012 [91]. Their analysis was based on Russian political discourse on Twitter collected between the 17th of March 2011 and the 12th of March 2012 via Twitter Streaming API.…”

Section: D: Other Topicsmentioning

confidence: 99%

The Applications of Sentiment Analysis for Russian Language Texts: Current Challenges and Future Perspectives

Smetanin

2020

IEEE Access

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Sentiment analysis has become a powerful tool in processing and analysing expressed opinions on a large scale. While the application of sentiment analysis on English-language content has been widely examined, the applications on the Russian language remains not as well-studied. In this survey, we comprehensively reviewed the applications of sentiment analysis of Russian-language content and identified current challenges and future research directions. In contrast with previous surveys, we targeted the applications of sentiment analysis rather than existing sentiment analysis approaches and their classification quality. We synthesised and systematically characterised existing applied sentiment analysis studies by their source of analysed data, purpose, employed sentiment analysis approach, and primary outcomes and limitations. We presented a research agenda to improve the quality of the applied sentiment analysis studies and to expand the existing research base to new directions. Additionally, to help scholars selecting an appropriate training dataset, we performed an additional literature review and identified publicly available sentiment datasets of Russian-language texts. INDEX TERMS Classification, machine learning, computational linguistics, sentiment analysis, applications of sentiment analysis, Russian-language texts, public opinion.

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“…As Frye and Borisova (2016) note, for example, in its coverage of the large protests of December 10 2011, state television did not report protesters' calls for Putin's resignation. Pro-government users also tried to marginalize the opposition online, across social media platforms (Spaiser et al 2017). examined the effect of regional protests on support for the demands of the protesters.…”

Section: Opposition Protests and Differentiation In Defectionsmentioning

confidence: 99%

Protests and Voter Defections in Electoral Autocracies: Evidence From Russia

Tertytchnaya

2019

Comparative Political Studies

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A large literature expects that as protests unfold in electoral autocracies, voters who supported the ruling regime in the past will withdraw support and shift to supporting its opponents. Yet there are only a few empirical tests of how opposition protests influence voter defections in these regimes. To gain empirical traction on this question, I draw on evidence from Russia. Tying together evidence from a protest-event dataset and a panel survey of voters conducted prior to and during the 2011-2012 protest wave, I examine how voters who supported the ruling regime in the past respond to anti-regime mobilization. Results reveal differentiation in defections. While opposition protests dampen support for the ruling regime and depress engagement, they do not necessarily translate into greater support for the regime’s challengers. Findings, which have implications for debates on defection cascades in autocracies, speak to the literatures on authoritarian endurance and the legacies of (attempted) revolutions.

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Communication power struggles on social media: A case study of the 2011–12 Russian protests

Cited by 60 publications

References 48 publications

Conflict forecasting and its limits

Conflict forecasting and its limits

The Applications of Sentiment Analysis for Russian Language Texts: Current Challenges and Future Perspectives

Protests and Voter Defections in Electoral Autocracies: Evidence From Russia

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