Abstract: Today’s modern life is completely based on Internet. Now a day’s people cannot imagine life without Internet. From last few years people share their views, ideas, information with each other using social networking sites. Such interchanges might include diverse sorts of substance such as text, image, audio and video data. One fundamental issue in today On-line Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now OSNs provide little support to this requirement. Hence Online Social Networks should be extremely secure and should protect the individual’s privacy. The Online Social Network provides the security measures but they were limited. While Socializing the user can access the profile of other members which are involved in social sites and even share data such as images, text, videos etc. One critical issue in user wall is to give users the capability to control the messages posted on their own personal space in order to avoid unwanted content to be displayed on their wall. To overcome this problem, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be matter-of-fact to their walls, and a Machine Learning based soft classifier automatically labelling messages in content-based filtering.

Keywords: On-line Social Networks (OSNs), Machine learning, short Text Classifier, content-based-filtering

PDF | DOI: 10.17148/IJARCCE.2020.9646

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