Social crisis detection using Twitter based text mining-a machine learning approach

Abstract

Social-media and blogs are increasingly used for social-communication, an idea and thought publishing platform. Public intentions, wisdom, problems, solutions, mental states are shared in social media. Text is being the best and the most common way to communicate over social networks. All kinds of data shared in social sites like Facebook, Twitter, and Microblogs. People from different pursuance uses these media to publish thoughts and convey messages through text. Consequently, occurrences in social life are rapidly discussed in social blogs in daily manner. This work aims at discovering ongoing social crisis from the Twitter data. Text mining technique and sentiment analysis were applied to detect the current social crisis from the social sites. Twitter data were collected to identify the recent social crisis. Furthermore, the identified crisis was compared to reputed newspapers. A hybrid method used to detect recent social issues resulted nicely. However, our proposed analysis shows identifying rate 89%, 95%, 83%, 53%, and 98% for the top 5 identified crisis accordingly in the date between 27 February and 11 March 2020. The strategy used in this study for the detection of recent social crisis will contribute to the social life and findings of crisis will be eliminated easily.

Bitcoin trading indicator: a machine learning driven real time bitcoin trading indicator for the crypto market

“…A Python package for text processing is called TextBlob [22]. It provides a fundamental API for doing common NLP tasks, such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, and translation, among others [23]. It is easier to understand and more enticing.…”

La ética informativa y el derecho de la información, ¿necesitan una nueva regulación?

“…-En relación a este mundo intercomunicado, no se puede dejar de citar el nacimiento y desarrollo de las redes sociales, que están posibilitando una relación social de primera magnitud; aunque desde el punto de vista estrictamente informativo tengan bastantes aspectos negativos, relacionados con la verdad, la objetividad, el respeto a los derechos ajenos y un largo etc. (Rahman et al, 2023).…”