Feature Alignment for the Analysis of Verbatim Text Transcripts
Dateien
Datum
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Sammlungen
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
In the research of deliberative democracy, political scientists are interested in analyzing the communication models of discussions, debates, and mediation processes with the goal of extracting reoccurring discourse patterns from the verbatim transcripts of these conversations. To enhance the time-exhaustive manual analysis of such patterns, we introduce a visual analytics approach that enables the exploration and analysis of repetitive feature patterns over parallel text corpora using feature alignment. Our approach is tailored to the requirements of our domain experts. In this paper, we discuss our visual design and workflow, and we showcase the applicability of our approach using an experimental parallel corpus of political debates.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
JENTNER, Wolfgang, Mennatallah EL-ASSADY, Bela GIPP, Daniel A. KEIM, 2017. Feature Alignment for the Analysis of Verbatim Text Transcripts. EuroVA 2017 : EuroVis Workshop on Visual Analytics. Barcelona, Spain, 12. Juni 2017 - 13. Juni 2017. In: SEDLMAIR, Michael, ed., Christian TOMINSKI, ed.. EuroVA 2017 : EuroVis Workshop on Visual Analytics. Goslar: Eurographics Association, 2017, pp. 13-18. ISBN 978-3-03868-042-0. Available under: doi: 10.2312/eurova.20171113BibTex
@inproceedings{Jentner2017Featu-39717, year={2017}, doi={10.2312/eurova.20171113}, title={Feature Alignment for the Analysis of Verbatim Text Transcripts}, isbn={978-3-03868-042-0}, publisher={Eurographics Association}, address={Goslar}, booktitle={EuroVA 2017 : EuroVis Workshop on Visual Analytics}, pages={13--18}, editor={Sedlmair, Michael and Tominski, Christian}, author={Jentner, Wolfgang and El-Assady, Mennatallah and Gipp, Bela and Keim, Daniel A.} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/39717"> <dc:creator>Keim, Daniel A.</dc:creator> <dcterms:abstract xml:lang="eng">In the research of deliberative democracy, political scientists are interested in analyzing the communication models of discussions, debates, and mediation processes with the goal of extracting reoccurring discourse patterns from the verbatim transcripts of these conversations. To enhance the time-exhaustive manual analysis of such patterns, we introduce a visual analytics approach that enables the exploration and analysis of repetitive feature patterns over parallel text corpora using feature alignment. Our approach is tailored to the requirements of our domain experts. In this paper, we discuss our visual design and workflow, and we showcase the applicability of our approach using an experimental parallel corpus of political debates.</dcterms:abstract> <dc:creator>Gipp, Bela</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:creator>El-Assady, Mennatallah</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>El-Assady, Mennatallah</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:contributor>Gipp, Bela</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/39717/1/Jentner_0-419041.pdf"/> <dc:rights>terms-of-use</dc:rights> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-08-01T11:15:51Z</dc:date> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/39717"/> <dc:creator>Jentner, Wolfgang</dc:creator> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/39717/1/Jentner_0-419041.pdf"/> <dc:language>eng</dc:language> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-08-01T11:15:51Z</dcterms:available> <dc:contributor>Jentner, Wolfgang</dc:contributor> <dcterms:title>Feature Alignment for the Analysis of Verbatim Text Transcripts</dcterms:title> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dcterms:issued>2017</dcterms:issued> </rdf:Description> </rdf:RDF>