Open Access
Issue
E3S Web Conf.
Volume 189, 2020
2020 International Conference on Agricultural Science and Technology and Food Engineering (ASTFE 2020)
Article Number 03019
Number of page(s) 5
Section Natural Resources and Environmental Studies
DOI https://doi.org/10.1051/e3sconf/202018903019
Published online 15 September 2020
  1. Lauzen, M. M., & Dozier, D. M. The Role of Women on Screen and behind the Scenes in the Television and Film Industries: Review of a Program of Research. Journal of communication inquiry, 23 (4), 355-373. (1999). [CrossRef] [Google Scholar]
  2. Lindasari, E., Ansari, K., & Marice, M.. Interactive Multimedia Development in Learning of Film Review Text for 8th Grade Students in Senior High School (SMP) 1 Tanjungmorawa. Budapest International Research and Critics in Linguistics and Education (BirLE) Journal, 2 (4), 355-362. (2019) [CrossRef] [Google Scholar]
  3. Alsaqer, A. F., & Sasi, S. Movie review summarization and sentiment analysis using rapidminer. In 2017 International Conference on Networks & Advances in Computational Technologies (NetACT) (pp. 329-335). IEEE. (2017, July). [CrossRef] [Google Scholar]
  4. Tripathi, A., & Trivedi, S. K.. Sentiment analyis of Indian movie review with various feature selection techniques. In 2016 IEEE International Conference on Advances in Computer Applications (ICACA) (pp. 181-185). IEEE. (2016, October) [Google Scholar]
  5. Khan, A., Gul, M. A., Zareei, M., Biswal, R. R., Zeb, A., Naeem, M., ... & Salim, N. Movie Review Summarization Using Supervised Learning and Graph-Based Ranking Algorithm. Computational Intelligence and Neuroscience, (2020) [Google Scholar]
  6. Sharma, S. S., & Dutta, G.. Polarity Determination of Movie Reviews: A Systematic Literature Review. International Journal of Innovative Knowledge Concepts, 6, 12. (2018) [Google Scholar]
  7. Brar, G. S., & Sharma, A. P. A.. Sentiment Analysis of Movie Review Using Supervised Machine Learning Techniques. International Journal of Applied Engineering Research, 13 (16), 12788-12791. (2018) [Google Scholar]
  8. Park, H. Y., & Kim, K. J.. Sentiment Analysis of Movie Review Using Integrated CNN-LSTM Mode. Journal of Intelligence and Information Systems, 25 (4), 141-154. (2019) [Google Scholar]

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