Emotion Dynamics of Public Opinions on Twitter
| Autor: | Sanasam Ranbir Singh, Sukumar Nandi, Durgesh Kumar, Eva Onaindia de la Rivaherrera, Debashis Naskar |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Internet privacy 02 engineering and technology Social issues Public opinion Politics Broadcasting (networking) Viral marketing 020204 information systems 0502 economics and business 0202 electrical engineering electronic engineering information engineering Social media Emotion transition Social dynamics business.industry 05 social sciences Social agreement Influence measure General Business Management and Accounting Opinion discussion Computer Science Applications Dynamics (music) 050211 marketing business LENGUAJES Y SISTEMAS INFORMATICOS Information Systems |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| Popis: | [EN] Recently, social media has been considered the fastest medium for information broadcasting and sharing. Considering the wide range of applications such as viral marketing, political campaigns, social advertisement, and so on, influencing characteristics of users or tweets have attracted several researchers. It is observed from various studies that influential messages or users create a high impact on a social ecosystem. In this study, we assume that public opinion on a social issue on Twitter carries a certain degree of emotion, and there is an emotion flow underneath the Twitter network. In this article, we investigate social dynamics of emotion present in users' opinions and attempt to understand (i) changing characteristics of users' emotions toward a social issue over time, (ii) influence of public emotions on individuals' emotions, (iii) cause of changing opinion by social factors, and so on. We study users' emotion dynamics over a collection of 17.65M tweets with 69.36K users and observe 63% of the users are likely to change their emotional state against the topic into their subsequent tweets. Tweets were coming from the member community shows higher influencing capability than the other community sources. It is also observed that retweets influence users more than hashtags, mentions, and replies. The work described in this article was carried out in the OSiNT Lab (https://www.iitg.ac.in/cseweb/osint/), Indian Institute of Technology Guwahati, India. The creation of the dataset used in this study was partly supported by the Ministry of Information and Electronic Technology, Government of India. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|