Open Access

Downloads

Download data is not yet available.

Abstract

The trend of technological development and increasing varieties of social media lead to the changes in people’s behaviors in society and forming online communities. Changes of human’s behaviors make many models of business, marketing, services and even the field of education, security, politicsl change from approaches to user management. Community of users on social networks influence behaviors, habits of each user involved in the community. Therefore, exploring community on social networks from many different data sources via analyzing exchanged contents will help know the user community’s behaviors which are reflected in the content and topics that users are interested in discussing in messages. In this paper, we propose a new model of discovering communities of users on social networks based on the topic model combined with Kohonen network. In the proposed model, we focus on discovering communities of users on social networks and analyzing the interested topics change of online community in each period of time. The proposed model is experimented with a set of vectors in interested topics of online users in higher education field.



Author's Affiliation
Article Details

Issue: Vol 19 No 1 (2016)
Page No.: 81-94
Published: Mar 31, 2016
Section: Engineering and Technology - Research article
DOI: https://doi.org/10.32508/stdj.v19i1.613

 Copyright Info

Creative Commons License

Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Ho, T., & Do, P. (2016). A New Model for Discovering Communities of Users on Social Network. Science and Technology Development Journal, 19(1), 81-94. https://doi.org/https://doi.org/10.32508/stdj.v19i1.613

 Cited by



Article level Metrics by Paperbuzz/Impactstory
Article level Metrics by Altmetrics

 Article Statistics
HTML = 1625 times
Download PDF   = 1044 times
Total   = 1044 times