Open Access
Issue
E3S Web Conf.
Volume 317, 2021
The 6th International Conference on Energy, Environment, Epidemiology, and Information System (ICENIS 2021)
Article Number 05013
Number of page(s) 8
Section Information System Management and Environment
DOI https://doi.org/10.1051/e3sconf/202131705013
Published online 05 November 2021
  1. “Digital 2020: 3.8 billion people use social media - We Are Social.” https://wearesocial.com/blog/2020/01/digital-2020-3-8-billion-people-use-social-media (accessed May 30, 2021) [Google Scholar]
  2. “Twitter and News: How people use Twitter to get news.” https://www.americanpressinstitute.org/publications/reports/survey-research/how-people-use-twitter-news/ (accessed May 30, 2021) [Google Scholar]
  3. F. Nurhuda, S. Widya Sihwi, and A. Doewes, “Analisis Sentimen Masyarakat terhadap Calon Presiden Indonesia 2014 berdasarkan Opini dari Twitter Menggunakan Metode Naive Bayes Classifier,” J. Teknol. Inf. ITSmart, vol. 2, no. 2, p. 35, doi: 10.20961/its.v2i2.630 (2016) [Google Scholar]
  4. V. A. Fitri, R. Andreswari, and M. A. Hasibuan, “ScienceDirect ScienceDirect Sentiment Analysis of Social Media Twitter with Case of Anti-LGBT Campaign in Indonesia using Naïve Bayes, Decision Tree, and Random Forest Algorithm ScienceDirect Sentiment Analysis of Social Media Twitter with Case of Anti-LGBT Campaign in Indonesia using Naïve Bayes, Decision Tree, and Random Forest Algorithm,” doi: 10.1016/j.procs.2019.11.181 (2019) [Google Scholar]
  5. M. S. Mubarok, A. Adiwijaya, and M. D. Aldhi, “Aspect-based sentiment analysis to review products using Naïve Bayes,” AIP Conf. Proc., vol. 1867, doi: 10.1063/1.4994463 (2017) [Google Scholar]
  6. “Coronavirus tweets NLP - Text Classification | Kaggle.” https://www.kaggle.com/datatattle/covid-19-nlp-text-classification (accessed May 30, 2021) [Google Scholar]
  7. H. Parveen and S. Pandey, “Sentiment analysis on Twitter Data-set using Naive Bayes algorithm,” in Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2016, Apr. 2017, pp. 416–419, doi: 10.1109/ICATCCT.2016.7912034 (2017) [Google Scholar]
  8. A. Goel, J. Gautam, and S. Kumar, “Real time sentiment analysis of tweets using Naive Bayes,” in Proceedings on 2016 2nd International Conference on Next Generation Computing Technologies, NGCT 2016, Mar. 2017, pp. 257–261, doi: 10.1109/NGCT.2016.7877424 (2017) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.