Data from the paper: Topic-Based Agreement and Disagreement in US Electoral Manifestos

Item Type:	Dataset
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 2013-2015)

DDC Classification:	004 Computer science, internet
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/
DOI:	https://doi.org/10.7801/241
Access (Controlled):	Unknown
Related Publication(s) in MADOC:	Menini Stefano und Nanni Federico und Ponzetto Simone Paolo und Tonelli Sara (2017), Topic-based agreement and disagreement in US electoral manifestos

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File	Filename / Infos	Link
	Archive Filename: EMNLP_data.zip	Download (923kB)
	Text Filename: README.txt	Download (2kB)

Date Deposited:	18 Sep 2017 08:12
Last Modified:	29 Feb 2024 20:19

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