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Paper Title : Twitter Spam Classification using Machine Learning Techniques

ISSN : 2395-1303
Year of Publication : 2020
10.29126/23951303/IJET-V6I2P20

Authors: -Geetanjali Sharma, S.Samyuktha,Ishita Dhar3 Golda Dilip

         


Abstract
Stream clustering methods and mechanisms are used to categorize between spam and non-spam tweets. These methods make the assumption of considering the neighbouring clusters are symmetric and classify on that basis. However, this assumption is not entirely correct because the clusters have asymmetric distribution and might not be micro in size. Here, incremental naive bayes classifiers can be used for the microclusters whose population exceeds a certain level . This paper will further focus on applying the algorithms like Decision tree classifier, Support Vector classifier, Random Forest Classifier, Naive Bayes classifier and K-neighbouring algorithm to the dataset .Then, the performance of the algorithms will be tested on the basis of precision, recall, accuracy and F1 measure. The compared results further aid in proving that naive Bayes has the chance of being a better algorithm to classify spam and non-spam tweets.

Reference
[1] Shradha Hirve, SwarupaKamble, “Twitter Spam Detection”, International Journal of Engineering Science and computing,vol 6 issue 10,Oct 2016. [2]Shinde Asha Ashokrao, Shital Y. Gaikwad, “Performance Evaluation of Machine Learning-Based Streaming Spam Tweets Detection”,International Journal of Innovative Research in Computer and Communication engineering, vol.5 Issue 1, Jan 2017, doi: 10.15680/IJICCE.2017.0501036 [3] Surendra Sedhai , Aixin Sun, “Semi-Supervised Spam Detection in Twitter Stream”,IEEE Transactions on Computational Social Systems ( Volume: 5 , Issue: 1 , March 2018 ),doi:10.1109/TCSS.2017.2773581 [4] Surendra Sedhai ,Aixin Sun, “Spam Tweet Detection using Machine Learning Spproach”,International Journal of Advance Research and Innovative Ideas in Education ( Volume: 4 , Issue: 3 , 2018),IJARIIE-ISSN(O)-2395-4396 [5] Faiza Masood, Ghana Ammad, Ahmad Almogren, Assad Abbas ,Hasan Ali Khattak ,Ikram UdDin,MohsenGuizani ,Mansour Zuair, “Spammer Detection and Fake User Identification on Social Networks”,IEEE Access ( Volume: 7 ),doi: 10.1109/ACCESS.2019.2918196

Keywords
Naive Bayes, machinelearning, spam and non-spam