Topic-based agreement and disagreement in US electoral manifestos


Menini, Stefano ; Nanni, Federico ; Ponzetto, Simone Paolo ; Tonelli, Sara


[img]
Preview
PDF
196_Paper (5).pdf - Published

Download (122kB)

URL: https://ub-madoc.bib.uni-mannheim.de/42490
Additional URL: http://emnlp2017.net/
URN: urn:nbn:de:bsz:180-madoc-424901
Document Type: Conference or workshop publication
Year of publication: 2017
Book title: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Page range: 2928-2934
Conference title: EMNLP 2017: Conference on Empirical Methods in Natural Language Processing
Location of the conference venue: Kopenhagen
Date of the conference: 07.-11.09.2017
Place of publication: Stroudsburg, PA
Publishing house: Association for Computational Linguistics
ISBN: 978-1-945626-83-8
Publication language: English
Institution: School of Business Informatics and Mathematics > Wirtschaftsinformatik III (Ponzetto 2016-)
Subject: 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.

Dieser Eintrag ist Teil der Universitätsbibliographie.

Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.




Metadata export


Citation


+ Search Authors in

+ Download Statistics

Downloads per month over past year

View more statistics



You have found an error? Please let us know about your desired correction here: E-Mail


Actions (login required)

Show item Show item