Sentiment Analysis of movie reviews using Microsoft Text Analytics and Google Cloud Natural Language API

Authors(4) :-S Jaswanth Sai Chowdary, Sk Waseem Farooq, Sk Abubakar Siddique, S Dinesh

Sentiment analysis is focused on the extraction of emotions and opinions of the people towards a particular topic from a structured, semi-structured or unstructured textual data. In this paper we focus our task of sentiment analysis on The Movie DB (TMDB) database which is an online database and contains information of movies, television shows and video games including cast, crew and reviews. We examine the sentiment expression to classify the polarity of the movie review on a scale of 1(highly disliked) to 5(highly liked) and perform feature extraction and ranking and use these features to train our multilabel classifier to classify the movie review into its correct label.We will collect the reviews for various movies and perform classification on them. The classification for the reviews are done based on score obtained for the text. We are using two approaches to generate scores for the reviews. These approaches are Microsoft cognitive services and Google cloud natural language API.Finally we are able to generate the scores and can classify them based on movie reviews.

Authors and Affiliations

S Jaswanth Sai Chowdary
Department of CSE, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India
Sk Waseem Farooq
Department of CSE, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India
Sk Abubakar Siddique
Department of CSE, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India
S Dinesh
Department of CSE, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India

Sentiment Analysis, TMDB database, Microsoft cognitive services, Google cloud natural language API, classification

  1. Sahu, T. P., & Ahuja, S. (2016). Sentiment analysis of movie reviews: A study on feature selection & classification algorithms. 2016 International Conference on Microelectronics, Computing and Communications (MicroCom).DOI:10.1109/microcom.2016.7522583
  2. Magdum, S. S., &Megha, J. V. (2017). Mining online reviews and tweets for predicting sales performance and success of movies. 2017 International Conference on Intelligent Computing and Control Systems(ICICCS).DOI:10.1109/iccons.2017.8250738
  3. https://developers.themoviedb.org/3/movies/get-movie-reviews
  4. https://azure.microsoft.com/en-in/services/cognitive-services/text-analytics/
  5. https://cloud.google.com/natural-language/
  6. Topal, K., & Ozsoyoglu, G. (2016). Movie review analysis: Emotion analysis of IMDb movie reviews. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).DOI:10.1109/asonam.2016.7752387 

Publication Details

Published in : Volume 5 | Issue 1 | January-February 2019
Date of Publication : 2018-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 147-150
Manuscript Number : CSEIT195130
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

S Jaswanth Sai Chowdary, Sk Waseem Farooq, Sk Abubakar Siddique, S Dinesh, "Sentiment Analysis of movie reviews using Microsoft Text Analytics and Google Cloud Natural Language API", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 1, pp.147-150, January-February-2019. Available at doi : https://doi.org/10.32628/CSEIT195130
Journal URL : http://ijsrcseit.com/CSEIT195130

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