Sentiment Analysis of Top Colleges in India Using Twitter Data

Authors(6) :-Pallavi S, Rachana C, Ramya K V, Vidyashree, Gangadhar Immadi, Dr. Jitendranath Mungara

Nowadays, peoples’ reviews and opinions that are available on various websites are one of the most critical factors in formulating our views and influencing the success of a brand, product or service. With the growth of social mediain the world, and because it is easily accessible, stakeholders often take to expressing their opinions on popular social media, namely Twitter. Even though twitter data is extremely informative, it presents uswith a challenge for analysis because of its large and disorganized nature. Here we are trying to dive into the novel domain of performing sentiment analysis of people’s opinions regarding top colleges in India. Machine learning is used to get a more accurate result.

Authors and Affiliations

Pallavi S
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
Rachana C
ISE Department, New Horizon College of Engineering, Bengaluru, Karnataka, India
Ramya K V
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
Dr. Jitendranath Mungara
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) : 852-854
Manuscript Number : CSEIT1723301
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Pallavi S, Rachana C, Ramya K V, Vidyashree, Gangadhar Immadi, Dr. Jitendranath Mungara , "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.852-854, May-June-2017.
Journal URL : http://ijsrcseit.com/CSEIT1723301

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