Facebook Page Spam detection using Support Vector Machines based on n-gram model
With social networks like Facebook, twitter reaching to the
common masses, these have become the best target for spammers.
The newest way to mislead and fraud viewers is Page Spam.
Viewers are deceived to click on links to spam their connections,
redirect to a fraudulent business or spread wrong information
about famous figures, organizations and causes.
This research aims to categorize such pages from authentic fan
pages using support vector machines and n gram models.
Further an attempt has been made to improve our findings by
some optimizations.
Keywords: Spam Detection, SVM, n-grams, Natural Language Processing, Page Spam
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ABOUT THE AUTHOR
Himani Chawla
I am a computer science student recently graduated from College of Engineering and Technology, Bikaner. My research interests include machine learning & natural language processing.
Himani Chawla
I am a computer science student recently graduated from College of Engineering and Technology, Bikaner. My research interests include machine learning & natural language processing.
