OntoBlogDis: A Knowledge-Centric Ontology Driven Socially Aware Framework for Influential Blogger Discovery

Blogging in present-day times has become a common form of voicing opinions and explaining them. Therefore, commercial interventions to advertise products and political interventions, to share a party's agendas, etc., have been started to come upon blogs. The bloggers also make money on this, and a lot of upcoming bloggers are now finding high-grossing blogs and further write about the same topic or paraphrase it to increase their views in a very short time. This does not help in the growth of this mode of media in a long run. Thus, by finding the influential blogger these problems can be solved. This paper proposes a statistical knowledge engineering-based approach to provide an effective solution to this problem. The proposed OntoBlogDis uses TF-IDF, Synonymization, NPMI for Term Co-occurrence, Static Ontology Matching using ANOVA, Jaccard similarity, and knowledge harvesting from Wikidata. OntoBlogDis when compared to the baselined approach is inferred to be superior and recorded an overall F-measure and FNR are 96.84% and 0.02.