Data from the paper: Topic-Based Agreement and Disagreement in US Electoral Manifestos
Item Type: | Dataset |
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Title: | Data from the paper: Topic-Based Agreement and Disagreement in US Electoral Manifestos |
Date: | 18 September 2017 |
Creator: | Menini, Stefano ; Nanni, Federico ; Ponzetto, Simone Paolo ; Tonelli, Sara |
Divisions: | Außerfakultäre Einrichtungen > SFB 884 School of Business Informatics and Mathematics > Semantic Web (Juniorprofessur) (Ponzetto 2013-15) |
DDC Classification: |
004 Computer science, internet |
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Abstract: | We present a topic-based analysis of agreement and disagreement in political manifestos, which relies on a new method for topic detection based on key concept clustering. Our approach outperforms both standard techniques like LDA and a state-of-the-art graph-based method, and provides promising initial results for this new task in computational social science. |
URL: | https://madata.bib.uni-mannheim.de/241/ |
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DOI: | https://doi.org/10.7801/241 |
Availability (Controlled): | Unknown |
Publication(s) (MADOC): |
Menini Stefano und Nanni Federico und Ponzetto Simone Paolo und Tonelli Sara (2017), Topic-based agreement and disagreement in US electoral manifestos |
File | Filename / Infos | Link |
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Archive
Filename: EMNLP_data.zip |
Download (923kB)
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Text
Filename: README.txt |
Download (2kB)
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Depositing User: | Federico Nanni |
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Date Deposited: | 18 Sep 2017 08:12 |
Last Modified: | 29 Feb 2024 20:19 |
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