Sentiment Analysis in Communication Studies: A Bibliographic Study on Web of Science Indexed Articles
Öz
Anahtar Kelimeler
Sentiment Analysis, Communication Studies, Bibliometric Analysis, Text Mining, Web of Science.
Etik Beyan
Kaynakça
- Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
- Asur, S., & Huberman, B. A. (2010). Predicting the Future with Social Media. 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 492–499. https://doi.org/10.1109/WI- IAT.2010.63
- Barkur, G., Vibha, & Kamath, G. B. (2020). Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India. Asian Journal of Psychiatry, 51, 102089. https://doi.org/10.1016/j.ajp.2020.102089
- Benoit, K. (2020). Text as Data: An Overview. In Luigi Curini & R. Franzese (Eds.), The SAGE Handbook of Research Methods in Political Science and International Relations. SAGE Publications Ltd. https://methods.sagepub.com/book/research-methods-in-political-science-and-international-relations
- Bermingham, A., & Smeaton, A. (2011). On using Twitter to monitor political sentiment and predict election results. 2–10.
- Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(Jan), 993–1022.
- Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008
- Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1–8. https://doi.org/10.1016/j.jocs.2010.12.007
- Ceron, A., Curini, L., Iacus, S. M., & Porro, G. (2014). Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens’ political preferences with an application to Italy and France. New Media & Society, 16(2), 340–358. https://doi.org/10.1177/1461444813480466
- Dahal, B., Kumar, S. A. P., & Li, Z. (2019). Topic modeling and sentiment analysis of global climate change tweets. Social Network Analysis and Mining, 9(1), 24. https://doi.org/10.1007/s13278-019-0568-8