Ontology-based text-mining model for social network analysis

Sam, K M and Chatwin, C R (2012) Ontology-based text-mining model for social network analysis. In: Management of Innovation and Technology (ICMIT), 2012 IEEE International Conference on. IEEE, pp. 226-231. ISBN 9781467301084

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Abstract

This paper aims to design a system model that analyzes the unstructured data inside the posts about electronic products on social networking websites. For the purposes of this study, posts on social networking websites have been mined and the keywords are extracted from such posts. The extracted keywords and the ontologies of electronic products and emotions form the base for the text-mining model which is used to understand online consumer behavior in the market.

Item Type: Book Section
Keywords: non-rule based unstructured data; ontology; query analysis; semantic content retrieval; social network analysis; text mining
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: H Social Sciences > HB Economic theory. Demography > HB0131 Methodology > HB0135 Mathematical economics. Quantitative methods Including econometrics, input-output analysis, game theory
H Social Sciences > HB Economic theory. Demography > HB3711 Business cycles. Economic fluctuations
H Social Sciences > HF Commerce
H Social Sciences > HT Communities. Classes. Races > HT0101 Urban groups. The city. Urban sociology > HT0388 Regional economics. Space in economics
Q Science > QA Mathematics
Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Z Bibliography. Library Science. Information Resources > ZA Information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
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Depositing User: Chris Chatwin
Date Deposited: 30 Aug 2012 08:39
Last Modified: 30 Aug 2012 08:39
URI: http://sro.sussex.ac.uk/id/eprint/40503
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