Classification of Messages in Online Social Network using Short Text Classifier

At present Online Social Networks (OSN) usually not provide much support to the user for message filtering. To rectify this issue, a work is proposed which allows OSN users to have a direct control on the messages posted on their walls. Here the users can control the messages posted on their own private space to avoid unwanted messages displayed and they can also block their friend from friends list. A new Global Vector Space Model (GVSM) is used here in text representation and pattern search based classifier is introduced for these OSNs which automatically labels messages in support of content-based filtering. The evaluation result shows the best performance of this study for message filtering in OSN, to customize the user walls and their profiles. Efficiency of this study is proved by the results of accuracy and elapsed time interval.