Title: Text mining for opinion analysis: the case of recent floods in Iran on Twitter

Authors: Reza Kamranrad; Ali Jozi; Ehsan Mardan

Addresses: Department of Industrial Engineering, Faculty of Engineering, Semnan University, Semnan, Iran ' Department of Industrial Engineering, Faculty of Engineering, Semnan University, Semnan, Iran ' Department of Industrial Engineering, Faculty of Engineering, Semnan University, Semnan, Iran

Abstract: The sentiment analysis relates to the study and understanding of emotions and beliefs in a particular text. This analysis gives us a lot of information. Twitter is a popular social network in recent years, in which users express their opinions and feelings about various topics in the Twitter social media operating system. By analysing this information, we can get an overview of public opinion about any particular topic. The classification of information is effective in understanding information and we cluster information. In this article, we are trying to analyse the status of Twitter on the monitoring and emotions of people about the recent flood events in Iran.

Keywords: text mining; Twitter; sentiment analysis; machine learning; language processing; NLP; Python; clustering.

DOI: 10.1504/IJBIDM.2022.122162

International Journal of Business Intelligence and Data Mining, 2022 Vol.20 No.3, pp.364 - 376

Received: 27 Feb 2020
Accepted: 01 Nov 2020
Published online: 11 Apr 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article