Ontology-Based Role Association Networks for Visualizing Trends in Political Debate

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Online resources, large data repositories and streaming social network messagesembed plenitudes of interesting knowledge, often of associative nature. A specific communicative context, such as the political debate in a given country, has groupings of actors, with changing attitudes and stancestowards each other and external, real or invented, threats and opportunities.A new form of associative network is introduced, that integrate flexible ontologiesfor complex contexts of roles and hierarchies with a labelled association structure representingobserved strengths and attitudes.Twitter messages from the political landscape in Denmark up to the general election 2015 are used asa both current and relevant illustrative case.
Original languageEnglish
Title of host publicationModeling and Using Context : 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6,2015. Proceedings
EditorsHenning Christiansen, Isidora Stojanovic, George A. Papadopoulos
PublisherSpringer
Publication date2015
Pages477-482
ISBN (Print)978-3-319-25590-3
ISBN (Electronic)978-3-319-25591-0
DOIs
Publication statusPublished - 2015
EventCONTEXT 15: International and Interdisciplinary Conference on Modeling and Using Context - Lordos Beach Hotel, Larnaca, Cyprus
Duration: 2 Nov 20156 Nov 2015
http://cyprusconferences.org/context2015/ (Link to conference)

Conference

ConferenceCONTEXT 15
LocationLordos Beach Hotel
CountryCyprus
CityLarnaca
Period02/11/201506/11/2015
Internet address
SeriesLecture notes in artificial intelligence
Volume9405
ISSN0302-9743

Cite this

Andreasen, T., Christiansen, H., & Eberholst, M. K. (2015). Ontology-Based Role Association Networks for Visualizing Trends in Political Debate. In H. Christiansen, I. Stojanovic, & G. A. Papadopoulos (Eds.), Modeling and Using Context: 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6,2015. Proceedings (pp. 477-482). Springer. Lecture notes in artificial intelligence, Vol.. 9405 https://doi.org/10.1007/978-3-319-25591-0_35
Andreasen, Troels ; Christiansen, Henning ; Eberholst, Mads Kæmsgaard. / Ontology-Based Role Association Networks for Visualizing Trends in Political Debate. Modeling and Using Context: 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6,2015. Proceedings. editor / Henning Christiansen ; Isidora Stojanovic ; George A. Papadopoulos. Springer, 2015. pp. 477-482 (Lecture notes in artificial intelligence, Vol. 9405).
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Andreasen, T, Christiansen, H & Eberholst, MK 2015, Ontology-Based Role Association Networks for Visualizing Trends in Political Debate. in H Christiansen, I Stojanovic & GA Papadopoulos (eds), Modeling and Using Context: 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6,2015. Proceedings. Springer, Lecture notes in artificial intelligence, vol. 9405, pp. 477-482, Larnaca, Cyprus, 02/11/2015. https://doi.org/10.1007/978-3-319-25591-0_35

Ontology-Based Role Association Networks for Visualizing Trends in Political Debate. / Andreasen, Troels; Christiansen, Henning; Eberholst, Mads Kæmsgaard.

Modeling and Using Context: 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6,2015. Proceedings. ed. / Henning Christiansen; Isidora Stojanovic; George A. Papadopoulos. Springer, 2015. p. 477-482.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Andreasen T, Christiansen H, Eberholst MK. Ontology-Based Role Association Networks for Visualizing Trends in Political Debate. In Christiansen H, Stojanovic I, Papadopoulos GA, editors, Modeling and Using Context: 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6,2015. Proceedings. Springer. 2015. p. 477-482. (Lecture notes in artificial intelligence, Vol. 9405). https://doi.org/10.1007/978-3-319-25591-0_35