K-Nearest Neighbor Classifier for Classifying user Reviews on Social Media Networks

Authors

  • Fahad Alotaibi Department of Information System, King Adulaziz University, Jaddah, KSA
  • Nashwan Ahmed Alromema 1-Department of Information System, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah Saudi Arabia 2-Department of Software Engineering, Faculty of Computing, Universiti Teknologi Malaysia, Skudai Johor, Malaysia

DOI:

https://doi.org/10.21015/vtcs.v10i1.1177

Abstract

Gigantic content generated on social media networking sites have made the online users enabled to communicate their opinions and sentiments about products and other entities like political events etc. Opinion mining applications aim to provide facilities to user and companies for know about products in which they are interested. In this work, opinion mining system for comparative reviews is developed using supervised machine learning approach. For this purpose, K-nearest neighbor classifier is trained on a publicly available dataset. Effectiveness of the system is validated by comparing its performance with other classifiers.

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Published

2022-06-30

Issue

Vol. 10 No. 1 (2022): January-June

Section

Articles

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