DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-8,Issue-5 ( May, 2021 ) | |||||||||
Paper Title |
Detecting Fake Trends in Twitter using Datamining and Text-mining Techniques | |||||||||
Author Name |
Alhanouf Alzamil, Modher Alhaq Abu Alhasanat | |||||||||
Affilition |
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Pages |
11-13 | |||||||||
Abstract |
Twitter is a wide platform used by people to express their opinions about a particular topic, product or service. Also, it is able to influence the work of the community and attracted a lot of attention. But sometimes Twitter's trends have been used to mislead people. In this paper, we will check and detect fake trends by collecting tweet trends and then analyzing and pre-processed the data collected by streaming API twitter and URLs. After that, we will use machine learning algorithm to determine all the fake trends in twitter. Classification algorithms “ a naïve byes” and other will use for the detection of fake trends. Keywords - Streaming API, URLs, Machine Learning, NaïVe Byes. | |||||||||
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