Leveraging social network analysis with topic models and the Semantic Web
Leveraging social network analysis with topic models and the Semantic Web
Social Network Analysis (SNA) and Web Mining (WM) techniques are being applied to study the structures of social networks in order to manage their dynamics and predict their evolution. This paper describes how we used Semantically-Interlinked Online Communities (SIOC) ontology to represent the (latent) semantic relationships between the members of a large community forum (about 2,500), Plexilandia. We extended SIOC, taking advantage of topic-based text mining and developed data mining algorithms that used our SIOC extensions to provide a better understanding of the social dynamics of the members of the Plexilandia community. This new understanding helped us to detect and discover the key members of Plexilandia successfully.
Rios, Sebastian
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Aguilera, Felipe
46384ff9-7bdf-4238-8181-8f785c9e87ca
Bustos, Francisco
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Omitola, Temitope
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Shadbolt, Nigel
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Rios, Sebastian
d69b7477-35e3-4b85-ae27-cd1a07109001
Aguilera, Felipe
46384ff9-7bdf-4238-8181-8f785c9e87ca
Bustos, Francisco
4d068559-103f-4dc5-b431-bbc8967e44dd
Omitola, Temitope
1c60a885-5485-4676-8907-d657c22d5f58
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Rios, Sebastian, Aguilera, Felipe, Bustos, Francisco, Omitola, Temitope and Shadbolt, Nigel
(2011)
Leveraging social network analysis with topic models and the Semantic Web.
International Workshop on Web Intelligence and Communities at the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2011), Lyon, France.
22 - 27 Aug 2011.
4 pp
.
(Submitted)
Record type:
Conference or Workshop Item
(Paper)
Abstract
Social Network Analysis (SNA) and Web Mining (WM) techniques are being applied to study the structures of social networks in order to manage their dynamics and predict their evolution. This paper describes how we used Semantically-Interlinked Online Communities (SIOC) ontology to represent the (latent) semantic relationships between the members of a large community forum (about 2,500), Plexilandia. We extended SIOC, taking advantage of topic-based text mining and developed data mining algorithms that used our SIOC extensions to provide a better understanding of the social dynamics of the members of the Plexilandia community. This new understanding helped us to detect and discover the key members of Plexilandia successfully.
Text
Srios_Omitola_WIC.pdf
- Accepted Manuscript
Available under License Other.
More information
Submitted date: 22 April 2011
Venue - Dates:
International Workshop on Web Intelligence and Communities at the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2011), Lyon, France, 2011-08-22 - 2011-08-27
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 272282
URI: http://eprints.soton.ac.uk/id/eprint/272282
PURE UUID: 417ab6b4-2eb1-47b7-999a-82c89cd84f58
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Date deposited: 13 May 2011 18:32
Last modified: 14 Mar 2024 09:51
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Contributors
Author:
Sebastian Rios
Author:
Felipe Aguilera
Author:
Francisco Bustos
Author:
Nigel Shadbolt
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