MAT JOURNALS
Published April 2, 2019 | Version v1
Journal article Open

Review on Sentiment Analysis of Twitter Data with Some Classifiers Ensembles

Creators

  • 1. UG Student, Department of Computer Science and Technology, Manav Rachna University, Faridabad, Haryana, India
  • 2. Assistant Professor, Department of Computer Science and Technology, Manav Rachna University, Faridabad, Haryana, India

Description

In the research paper, the focus is on the citizen’s emotions towards different organization, brands, and on the different interests. By Sentimental Analysis on twitter, which give the attractive and speedy way to the people to enjoy the above mentioned different things. Apart from the Sentimental Analysis, the semantic approach is to increase the features and get more accurate results. These are just applying some techniques to differentiate the twitter analysis’s data. By this, the result shows some harmonic score to investigate the positive and negative data.

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Additional details

References

  • Hassan Saif, Yulan He and Harith Alani.: Knowledge Media Institute, The Open University, United Kingdom
  • Speriosu, M., Sudan, N., Upadhyay, S., Baldridge, J.: Twitter polarity classification with labelpropagationoverlexicallinksandthefollowergraph
  • Kouloumpis, E., Wilson, T., Moore, J.: Twitter sentiment analysis: Thegood the bad andthe omg
  • Barbosa, L., Feng, J.: Robust sentiment detection on twitter from biased and noisy data
  • Lei Zhang, RiddhimanGhosh, Mohamed Dekhil, Meichun Hsu, Bing Liu " Combining Lexicon-based and Learning-based Methods for Twitter Sentiment Analysis" 2011
  • Alexander Pak, Patrick Paroubek "Twitter as a Corpus for Sentiment Analysis and Opinion Mining" 2010
  • XiaolongWang, Furu Wei, Xiaohua Liu, Ming Zhou, Ming Zhang "A Graph-based Hashtag Sentiment Classification Approach" 2011

Subjects

Computer Science / IT Journals
http://matjournals.com/Engineering-Journals.html