Filtering Online Social Networks Based on User Content Generation
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Date
2017-03
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Volume Title
Publisher
International Journal of Advanced Research in Computer Science and Software Engineering
Abstract
Social media is part of computer mediated technology that helps an individual to connect with their friends, family and online society, to share information, ideas, career interests and other forms of expressions. Online social networks (OSN) are facing the problem of the people posting indecent messages on individual's wall. Machine learning (ML) intelligence is used to filter these large volumes of data. I aim to propose an automated filter war (FW), able to filter unwanted messages from (OSN) user walls. To the fact that in OSN’s there is the possibility of posting and giving comments on other posts on particular public (or) private walls (PW). Information filtering is mainly used to give user the ability to control the kind of information written on their own walls by filtering out unwanted messages from a chunk of data that a user intends to post. Content Based Filtering will give user ability to select information item based on the correlation between the content of the items and the user preferences. On the other hand Filtering will be mainly used to filter the unwanted messages and if tendency is noticed from the person posting messages, option of blacklisting is available.
Description
Journal Article
Keywords
Online social networks, filter wall, private wall, machine learning.
Citation
Okemwa, J. G. (2017). Filtering Online Social Networks Based on User Content Generation. International Journal of Advanced Research in Computer Science and Software Engineering