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A Novel Technique for Authorship Verification of Hijacked Online Social Networks User Accounts

Journal: International Journal of Science and Research (IJSR) (Vol.11, No. 3)

Publication Date:

Authors : ; ;

Page : 1275-1279

Keywords : Online social networks; hijacking attacks; Hijacked Social Media Accounts; feature extraction; machine learning; classification; LSTM;

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The Web has a huge amount of data accessible for internet users, and a large amount of data is also produced, thanks to the development and expansion of web technology. The Internet has become an online learning platform to exchange ideas and share views. Social networking services like Twitter, Facebook, and Google+ quickly acquire popularity since they enable users to exchange opinions on issues, talk with other groups or post messages worldwide. The expanded usage of Online Social Network (OSN) has become necessary to appear to grow Authorship Verification (AV), OSN is the environment in which users can connect with other users to discuss ideas of any topics then expand data and information. AV is considered as a resource of researches and information in different ways, as is the case Sentiment Analysis (SA). In this paper, the proposed technique is compared with the previous feature extraction technique which was inefficient in providing better results comprised of the Tweets API dataset. Twitter is a popular website for social networking users posting and interacting with "tweets". The new model is henceforth capable to provide better accuracy.

Last modified: 2022-05-14 21:02:36