Sentiment Analysis of Top Colleges in India Using Twitter Data

Authors(5) :-Pallavi. S, Ramya K.V, Rachana C, Vidyashree, Gangadhar Immadi

Sentiment analysis is used for identifying and classifying opinions or sentiments expressed in source text. Social media is generating a vast amount of sentiment rich data in the form of tweets, status updates, blog posts etc. Sentiment analysis of this user generated data is very useful in knowing the opinion of the crowd [6]. Due to the presence of slang words and misspellings, twitter sentiment analysis is difficult compared to general sentiment analysis. Sentiments from the source text will be analyzed by using a machine learning approach. Mining opinions and analyzing sentiments from social network data which will help in several fields such as even prediction, analyzing overall mood of public on a particular social issue. The accuracy of classification can be increased by using Natural Language Processing (NLP) Techniques. We present a new feature vector for classifying the tweets as positive, negative, neutral and undefined. The mined text information is subjected to Ensemble classification to analyze the sentiment. Ensemble classification involves combining the effect of various independent classifiers on a particular classification problem [1]. Multi-Layer Perceptron (MLP) is used to classify the features extracted from the reviews. A Decision Tree-based Feature Ranking is used for feature selection. Based on Manhattan Hierarchical Cluster Criterion the ranking will be done [5].

Authors and Affiliations

Pallavi. S
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
Ramya K.V
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
Rachana C
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
Vidyashree
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
Gangadhar Immadi
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India

Sentiment Analysis, Machine Learning, Opinion Mining, Natural Language Processing Twitter, Multilayer perceptron(MLP).

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Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 2017-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 689-693
Manuscript Number : CSEIT172340
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Pallavi. S, Ramya K.V, Rachana C, Vidyashree, Gangadhar Immadi, "Sentiment Analysis of Top Colleges in India Using Twitter Data", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.689-693, May-June-2017.
Journal URL : http://ijsrcseit.com/CSEIT172340

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