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Topics2Themes: Computer-Assisted Argument Extraction by Visual Analysis of Important Topics
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). University of Potsdam, Germany. (ISOVIS)ORCID-id: 0000-0001-6164-7762
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). (ISOVIS)ORCID-id: 0000-0002-1907-7820
University of Potsdam, Germany.
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). (ISOVIS)ORCID-id: 0000-0002-0519-2537
2018 (engelsk)Inngår i: Proceedings of the LREC 2018 Workshop “The 3rd Workshop on Visualization as Added Value in the Development, Use and Evaluation of Language Resources (VisLR III)” / [ed] Mennatallah El-Assady, Annette Hautli-Janisz, and Verena Lyding, Paris, France: European Language Resources Association, 2018, s. 9-16Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

While the task of manually extracting arguments from large collections of opinionated text is an intractable one, a tool for computerassisted extraction can (i) select a subset of the text collection that contains re-occurring arguments to minimise the amount of text that the human coder has to read, and (ii) present the selected texts in a way that facilitates manual coding of arguments. We propose a tool called Topics2Themes that uses topic modelling to extract important topics, as well as the terms and texts most closely associated with each topic. We also provide a graphical user interface for manual argument coding, in which the user can search for arguments in the texts selected, create a theme for each type of argument detected and connect it to the texts in which it is found. Topics, terms, texts and themes are displayed as elements in four separate lists, and associations between the elements are visualised through connecting links. It is also possible to focus on one particular element through the sorting functionality provided, which can be used to facilitate the argument coding and gain an overview and understanding of the arguments found in the texts.

sted, utgiver, år, opplag, sider
Paris, France: European Language Resources Association, 2018. s. 9-16
Emneord [en]
argument extraction, topic modelling, text analysis, argument visualization, stance visualization, text visualization, information visualization, interaction
HSV kategori
Forskningsprogram
Datavetenskap, Informations- och programvisualisering
Identifikatorer
URN: urn:nbn:se:lnu:diva-70911ISBN: 979-10-95546-13-9 (tryckt)OAI: oai:DiVA.org:lnu-70911DiVA, id: diva2:1182842
Konferanse
3rd Workshop on Visualization as Added Value in the Development, Use and Evaluation of Language Resources (VisLR III) at LREC '18, 12 May, 2018, Miyazaki, Japan
Prosjekter
StaViCTA
Forskningsfinansiär
Swedish Research Council, 2012-5659Swedish Research Council, 2016-06681Tilgjengelig fra: 2018-02-14 Laget: 2018-02-14 Sist oppdatert: 2019-11-13bibliografisk kontrollert

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Skeppstedt, MariaKucher, KostiantynKerren, Andreas

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