Munir Ahmad

Work place: Department of Computer Science, Virtual University of Pakistan



Research Interests: Data Mining, Data Structures and Algorithms


Munir Ahmad is MS scholar in Computer Science Department of Virtual University of Pakistan. He is working as Executive Director/ Head of IT Department in United International Group, Lahore, Pakistan. His area of research is Data Mining.

Author Articles
Analyzing the Performance of SVM for Polarity Detection with Different Datasets

By Munir Ahmad Shabib Aftab

DOI:, Pub. Date: 8 Oct. 2017

Social media and micro-blogging websites have become the popular platforms where anyone can express his/her thoughts about any particular news, event or product etc. The problem of analyzing this massive amount of user-generated data is one of the hot topics today. The term sentiment analysis includes the classification of a particular text as positive, negative or neutral, is known as polarity detection. Support Vector Machine (SVM) is one of the widely used machine learning algorithms for sentiment analysis. In this research, we have proposed a Sentiment Analysis Framework and by using this framework, analyzed the performance of SVM for textual polarity detection. We have used three datasets for experiment, two from twitter and one from IMDB reviews. For performance evaluation of SVM, we have used three different ratios of training data and test data, 70:30, 50:50 and 30:70. Performance is measured in terms of precision, recall and f-measure for each dataset.

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