Detecting Spam in Twitter and Email using Machine Learning Approach
Sneha Linganur · International Journal for Research in Applied Science and Engineering Technology · 2019
Online social Networks have turned out to be increasingly famous in the global.Individuals utilize these social platforms (e.g., Facebook, Twitter, etc.) for storing and sharing their personal information, activities, views, documents, posts and so on.At the same time, Social spam turned into an incessant issue nowadays which is incredibly hazardous to both individual clients and companies.Therefore, it is an imperious need to develop more accurate and powerful spam recognition models.This Paper essentially centers around machine Learning technique for distinguishing spam in Twitter and Email so as to make it increasingly secure.We choose twitter and email as our study targets.We apply Naive Bayes algorithm for discovery of spam using techniques such as preprocessing, word extraction by taking emails and real-time tweets as input to our project.The outcomes show an efficacious classification of spam and non-spam.Finally, we verify the perceptibility of spam tweets and mails as well as accounts through evaluation.Our proposed method could accomplish better outcomes contrasted with other existing supervised machine learning methods.