Identifying the influential bloggers: a modular approach based on sentiment analysis
Year: 2017
Type: article
Abstract: The social web provides an easy and quick medium for public communication and online social interactions. In the web log, short as a blog, the bloggers share their views in the form of creating and commenting on blog posts. The bloggers who influence other users in a blogging community are known as the influential bloggers. Identification of such influential bloggers has vast applications in advertising, online marketing and e-commerce. This paper investigates the problem of identifying influential bloggers and presents a model which consists of two modules: Activity and Recognition. The activity module takes into account a blogger's activity and recognition module measures a blogger's influence in his/her social community. The integration of activity and recognition modules identifies the active as well as influential bloggers. The proposed model, MIBSA (Model to find Influential Bloggers using Sentiment Analysis), takes into account the existing and novel features of sentiment expressed in content generated by a blogger. The model is evaluated against the existing standard models using the real world blogging data. The results confirm that sentiment expressed in blog content plays an important role in measuring a blogger's influence and should be considered as a feature for finding the top influential bloggers in the blogosphere.
Source: Journal of Web Engineering
Authors: Umar Ishfaq, Hikmat Ullah Khan, Khalid Iqbal
Institution: COMSATS University Islamabad
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2739769606