Detecting Vulnerable User in Twitter Using Tweet Description Logic Rule Generation
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2018, Vol 20, Issue 5
Abstract
In today’s modern era, Social media have become a mandatory, exciting and mundane apparatus in our lives and diverse informal organizations have distinctive focused set of people. Among these networks, twitter standout in the top list that has nearly 313 million dynamic clients on a monthly basis with a whopping 500 million of tweets each day. The commonly shared information on Twitter varies from current affairs, occasions, superstars in every field to government or political issues. Therefore, there is a need to conduct targeted research on identifying approaches for vulnerable user identification in twitter. The proposed system is used in identifying the maximum set of profile data that are necessary for identifying vulnerable user in twitter and identify the appropriate data mining approach for such task. The proposed system is used in identifying the maximum set of profile data that are necessary for identifying vulnerable user in twitter and identify the appropriate data mining approach for such task. This research has been proposed with data mining techniques of Tweet Description Logic Rule Generation algorithm for finding and analysis to the vulnerable user and attackers. Such profiles are distinguished by implementing the above algorithm which considers the targeted user followers and the sharing Threshold Limit as its parameters. Trial results assures of following: The suggested technique beats different models in regard of accuracy, efficiency and least time. Also, the assessment reveals that the identification rate of current method is significantly more compared to other methods.
Authors and Affiliations
S. Revathi, Dr. M. Suriakala
Keywords
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- EP ID EP402115
- DOI 10.9790/0661-2005022735.
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