AUTHOR=Das Swarna , Anwar Md Musfique 

TITLE=Discovering Topic-Oriented Highly Interactive Online Communities

JOURNAL=Frontiers in Big Data

VOLUME=2

YEAR=2019

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2019.00010

DOI=10.3389/fdata.2019.00010

ISSN=2624-909X

ABSTRACT=<p>Community detection is an interesting field of online social networks. Most existing approaches either consider common attributes of social network users or rely on only social connections among the users. However, not enough attention is paid to the degree of interactions among the community members in the retrieved communities, resulting in less interactive community members. This inactivity will create problems for many businesses as they require highly interactive users to efficiently advertise their marketing information. In this paper, we propose a model to detect topic-oriented densely-connected communities in which community members have active interactions among each other. We conduct experiments on a real dataset to demonstrate the effectiveness of our proposed approach.</p>