Sudhir Kumar Sharma

Work place: KIIT College of Engineering, Gurgaon, India



Research Interests: Computational Learning Theory, Neural Networks, Computer Networks


Dr. Sudhir Kumar Sharma obtained M.Tech degree in Computer Science and Engineering from Guru Jambheshwar University, Hisar, India in 1999 and Ph.D degree from USICT, GGSIP University, Delhi, India in 2013. He is currently working as a professor and Head of the Computer Science and Engineering Department at KIIT  College of Engineering, Gurgaon, India. His research area includes Machine Learning, Neural Networks, Text mining and analysis and AI systems.

Author Articles
Sentiment Predictions using Support Vector Machines for Odd-Even Formula in Delhi

By Sudhir Kumar Sharma Ximi Hoque

DOI:, Pub. Date: 8 Jul. 2017

This paper analyzes the odd-even formula in Delhi using tweets posted on Twitter from December 2015 to August 2016. Twitter is a social network where users post their feelings, opinions and sentiments for any event using hashtags and mentions. The tweets posted publicly can be viewed by anyone interested. This paper transforms the unstructured tweets into structured information using open source libraries. Further objective is to build a model using Support Vector Machines (SVM) to classify unseen tweets on the same context. This paper collects tweets on this event under the hashtag “#oddeven formula”. This study explores four freely available resources in the form of Application Programming Interfaces (APIs)/Packages for labeling tweets for academic research. Four machine learning models using SVM multi-class classifier were built using the labels provided by the APIs/Packages. The performances of these four models are evaluated through standard evaluation metrics. The experimental results reveal that TextBlob and Pattern python packages outperformed Vivekn and Meaning Cloud APIs. This study may also help in decision making of this event to some extent.

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