A challenge of managing and extracting useful knowledge from social mediadata sources has attracted much attention from academic and industry. Toaddress this challenge, semantic analysis of textual data is focused in thispaper. We propose an ontology-based approach to extract semantics of textualdata and define the domain of data. In other words, we semantically analyse thesocial data at two levels i.e. the entity level and the domain level. We havechosen Twitter as a social channel challenge for a purpose of concept proof.Domain knowledge is captured in ontologies which are then used to enrich thesemantics of tweets provided with specific semantic conceptual representationof entities that appear in the tweets. Case studies are used to demonstratethis approach. We experiment and evaluate our proposed approach with a publicdataset collected from Twitter and from the politics domain. The ontology-basedapproach leverages entity extraction and concept mappings in terms of quantityand accuracy of concept identification.
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