International Journal of Advance Computational Engineering and Networking (IJACEN)
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Statistics report
Aug. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 87
Paper Published : 1231
No. of Authors : 3095
  Journal Paper

Paper Title
A System To Detect Inappropriate Messages In Online Social Networks

Abstract
As social networking is growing at a rapid pace, it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Soft Text Classifier approach using various Machine Learning algorithms. The proposed system acts as a screening mechanism that alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults. Keywords- Machine Learning, Online Social Networks, Soft Text Classifier, Support Vector Machine.


Author - Rohan Shetty, Kalyani Nair, Shivani Singh, Shantanu Nakhare, Gopal Upadhye

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| Published on 2015-03-03
   
   
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