Cyber bullying is a rapidly burgeoning phenomenon in to-days world dominated by the Internet. From every major incident happening around the world to meager day-to-day activities of an individual is posted on social media. Ergo, Internet has now become an essentiality that is indispensable. Though this seems intriguing, however, it has led to the advent of cyber bullying. Social networking sites provide an easy platform for the cyber bullies to identify and victimize other users. Cyber bullies may make use of victims personal data(e.g. real name, home address) to impersonate them, or by creating fake accounts in social networking sites that defames, discredits or ridicules them. Due to the anonymity of the Cyber bullies it becomes increasingly difficult for the o ender to be caught and punished for their behavior. This paper proposes a system which identifies posts which are aimed at hurting the sentiments of other users and makes the user to rethink and hence refrain from posting the same. This paper also provides an effective algorithm that identifies and reduces the spam content in the users post/tweet. © Research India Publications.
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H. A. Raman, MuraliKrishnan, E., Abishek, M., SaiSandhesh, R., Vijaykanth, K., and Dr. Harini N., “Analysis of twitter feeds using natural language processing and machine learning”, International Journal of Applied Engineering Research, vol. 10, pp. 18911-18916, 2015.