Ontology-based approach for identifying the credibility domain in social Big Data. Issue 4 (2nd October 2018)

• Record Type: Journal Article
• Authors: Wongthongtham, Pornpit; Salih, Bilal Abu
• Is Part Of: Journal of organizational computing and electronic commerce. Volume 28:Issue 4(2018)
• Page Start: 354
• Page End: 377
• Publication Date: 2018-10-02
• Subjects: Semantic data extraction -- ontology -- social Big Data -- social media -- data analytics -- Twitter -- alchemyapi -- Watson; Management -- Data processing -- Periodicals; Electronic commerce -- Periodicals; Electronic data interchange -- Periodicals; Business enterprises -- Computer networks -- Periodicals; 658.0505
• DOI: 10.1080/10919392.2018.1517481
• Languages: English
• ISSNs: 1091-9392

Abstract

ABSTRACT: The challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academics and industry. To address this challenge, semantic analysis of textual data is focused on in this paper. We propose an ontology-based approach to extract semantics of textual data and define the domain of data. In other words, we semantically analyze the social data at two levels: the entity level and the domain level. We have chosen Twitter as a social channel for the purpose of concept proof. Ontologies are used to capture domain knowledge and to enrich the semantics of tweets, by providing specific conceptual representation of entities that appear in the tweets. Case studies are used to demonstrate this approach. We experiment and evaluate our proposed approach with a public dataset collected from Twitter and from the politics domain. The ontology-based approach leverages entity extraction and concept mappings in terms of quantity and accuracy of concept identification.