CFP last date
20 May 2024
Reseach Article

Sentiment Analysis for Visuals using Natural Language Processing

by Hari Iyer, Mihir Gandhi, Sindhu Nair
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 6
Year of Publication: 2015
Authors: Hari Iyer, Mihir Gandhi, Sindhu Nair
10.5120/ijca2015906581

Hari Iyer, Mihir Gandhi, Sindhu Nair . Sentiment Analysis for Visuals using Natural Language Processing. International Journal of Computer Applications. 128, 6 ( October 2015), 31-35. DOI=10.5120/ijca2015906581

@article{ 10.5120/ijca2015906581,
author = { Hari Iyer, Mihir Gandhi, Sindhu Nair },
title = { Sentiment Analysis for Visuals using Natural Language Processing },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 6 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 31-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number6/22879-2015906581/ },
doi = { 10.5120/ijca2015906581 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:20:42.983988+05:30
%A Hari Iyer
%A Mihir Gandhi
%A Sindhu Nair
%T Sentiment Analysis for Visuals using Natural Language Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 6
%P 31-35
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the aim is to build a hybrid Word Sense Disambiguation(WSD) technique, which is acutely focused on text associated with a certain form of visual. Natural language processing helps establish a context among the data elements that are aggregated to establish a certain meaning. Analyzing transcripts of visuals being uploaded in real-time saves resources and time required to sort content based on genres or emotions. The training data lays a foundation to rate the polarities of elements, on top of which the dictionary expands as an when new content is supplied to the apparatus. Third-party intelligence is combined with the dictionary to experience growth even when the consumer usage is idle. All these entities are mutually intertwined to ensure maximum utility and output.

References
  1. Manisha Kanakaraj and Ram Mohana Reddy Guddeti, “Performance Analysis of Ensemble Methods on Twitter Sentiment Analysis using NLP Techniques,” in IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015), February 7-9, 2015.
  2. M. Rajani Shree and Dr. Shanbhavi B.R, “Performance Comparison of Word Sense Disambiguation Approaches for Indian Languages”, in IEEE International Advance Computing Conference (IACC), 2015.
  3. Lakshmish Kaushik, Abhijeet Sangwan and John H. L. Hansen, “Automatic Sentiment Extraction from Youtube Videos”, in IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2013.
  4. Ms Kranti Ghag and Dr. Ketan Shah, “Comparative Analysis of the Techniques for Sentiment Analysis”, at ICATE 2013.
  5. Jose Costa Pereira, Jordi Luque and Xavier Anuera, “Sentiment Retrieval on Web Reviews Using Spontaneous Natural Speech”, in the 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP).
  6. Ankit Kumar, Mohit Dua, Arun Choudhary, “Implementation and performance evaluation of continuous Hindi speech recognition”, at the Electronics and communication systems (ICECS), 2014.
  7. Zohreh Madhoushi, Abdul Razak Hamdan, Suhaila Zainudin, “Sentiment Analysis Techniques in Recent Works”, at the Science and Information Journal in 2015.
  8. Haruna Isah, Paul Trundle, Daniel Neagu, “Social Media Analysis for Product Safety using Text Mining and Sentiment Analysis”, at the Computational Intelligence (UKCI), 2014 14th UK Workshop.
  9. Farhan Hassan Khan, Usman Qamar, M.Younus Javed, “SentiView: A Visual Sentiment Analysis Framework” at the International Conference on Information Society (i-Society 2014).
  10. Monisha Kanakaraj , Sowmya Kamath S, “NLP based Intelligent News Search Engine using Information Extraction from e-Newspapers” at the 2014 IEEE International Conference on Computational Intelligence and Computing Research.
Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Third-party intelligence Training Data Polarity Word Sense Disambiguation.