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SIFT – A language technology toolkit to assess the print media coverage of new forms of governance
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In: Wüest, Bruno; Amsler, Michael; Schneider, Gerold (2017). SIFT – A language technology toolkit to assess the print media coverage of new forms of governance. Working paper series / NCCR-Democracy 95, University of Zurich. NCCR-Democracy. (2017)
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Legitimacy of New Forms of Governance in Public Discourse - An Automated Media Content Analysis Approach Driven by Techniques of Computational Linguistics ...
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Legitimacy of New Forms of Governance in Public Discourse - An Automated Media Content Analysis Approach Driven by Techniques of Computational Linguistics
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In: Amsler, Michael; Wüest, Bruno (2016). Legitimacy of New Forms of Governance in Public Discourse - An Automated Media Content Analysis Approach Driven by Techniques of Computational Linguistics. In: PolText 2016. International Conference on the Advances in Computational Analysis of Political Text, Dubrovnik, 14 July 2016 - 16 July 2016, 1-7. (2016)
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Measuring the public accountability of new modes of governance ...
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Measuring the public accountability of new modes of governance
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In: Wüest, Bruno; Schneider, Gerold; Amsler, Michael (2014). Measuring the public accountability of new modes of governance. In: ACL Workshop on Language Technologies and Computational Social Science, Baltimore, MD, USA, 26 June 2014 - 26 June 2014, 38-43. (2014)
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Measuring the Public Account- ability of New Modes of Governance
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In: Wüest, Bruno; Schneider, G; Amsler, Michael (2014). Measuring the Public Account- ability of New Modes of Governance. In: ACL Workshop on Language Technology and Computational Social Science, Baltimore, Maryland, USA, 24 June 2014 - 26 June 2014. (2014)
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Using computational linguistics to enhance protest event analysis ...
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Using computational linguistics to enhance protest event analysis
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In: Wüest, Bruno; Rothenhäusler, Klaus; Hutter, Swen (2013). Using computational linguistics to enhance protest event analysis. In: ENCoRe Workshop 'Tools and Techniques for Conflict Event Data Collection', Konstanz, 6 December 2013 - 7 December 2013. (2013)
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Abstract:
For now more than four decades, quantitative protest event analysis (PEA) has routinely contributed to the testing and refinement of theories on political processes from different perspectives. However, it is commonly agreed that PEA data face serious challenges regarding their data sources. Precisely, researchers applying PEA struggle with the fact that they cannot use multiple sources for large geographical areas and long time periods. As a consequence, most of the scholarship still focuses on a narrow set of European countries or the United States and does not cover the period since the early 2000s. We are bringing PEA and computational linguistics together to suggest and evaluate an approach that will enable political scientists to extend their research designs with a more efficient and at the same time reliable data collection. The approach relies on hidden topic models, word space models, and named entity recognition to identify and code protest events.
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Keyword:
320 Political science; Institute of Political Science
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URL: https://doi.org/10.5167/uzh-150416 https://www.zora.uzh.ch/id/eprint/150416/1/ZORA150416.pdf https://www.zora.uzh.ch/id/eprint/150416/
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Replication data for: Electoral Campaigns and Relation Mining: Extracting Semantic Network Data from Newspaper Articles ...
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Electoral Campaigns and Relation Mining: Extracting Semantic Network Data from Newspaper Articles
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In: Wüest, Bruno; Clematide, S; Bünzli, A; Laupper, D; Frey, T (2011). Electoral Campaigns and Relation Mining: Extracting Semantic Network Data from Newspaper Articles. Journal of Information Technology & Politics, 8(4):444-463. (2011)
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