A Framework for Real-Time Spam Detection in Twitter
Abstract
A framework for real-time spam detection in Twitter management project report on web mining With millions of users tweeting around the world, real time search systems and different types of mining tools are emerging to allow people tracking the repercussion of events and news on Twitter project report.
However Twitter management project report on web mining , although appealing as mechanisms to ease the spread of news and allow users to discuss events and post their status, these services open opportunities for new forms of spam. Trending topics, the most talked about items on Twitter management project report on web mining at a given point in time, have been seen as an opportunity to generate traffic and revenue. Spammers post tweets containing typical words of a trending topic and URLs, usually obfuscated by URL shorteners, that lead users to completely unrelated websites.
Conclusion
A framework for real-time spam detection in Twitter management project report on web mining Many methods have been developed and used by various researchers to find out spammers in different social networks. From the A framework for real-time spam detection in Twitter management project report on web mining papers reviewed it can be concluded that most of the work has been done using classification approaches like SVM, Decision Tree, Naive Bayesian, and Random Forest. Twitter management project report on web mining Detection has been done on the basis of user based features or content based features or a combination of both.
| Project Name | A Framework for Real-Time Spam Detection in Twitter |
| Project Category | Web mining and Security |
| Project Cost | 65 $/ Rs 4999 |
| Delivery Time | 48 Hour |
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