Abstract
References
- BusinessofApp. [Online]. Available: https://www.businessofapps.com/data/twitter-statistics/. [Accessed: 13 June 2023].
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Abstract
Social media is attracting so many people from different demographics. Facebook, YouTube, TikTok, WhatsApp, Instagram, and LinkedIn are some of those. Each one has some similarities as well as some differences. Twitter is one of the most popular social media platforms. It was publicly launched to be used for micro-blogging in 2006. Originally, it was limited to a maximum of 140 characters. It extended its usage capacity and became one of the most highly used social media platforms. Twitter users reached around 401 million by 2022. According to statistics, the number of daily tweets shared on Twitter is 500 million. The contents of shared tweets are so valuable for data analytic since they provide information about such as users' social lives, feelings, political opinions, and social environment. In this study, it is intended to introduce a visualization platform for Twitter data to provide better analysis. By using this tool, it will be possible to have a better understanding of the big data produced by Twitter posts. Analysis of all of the actions of Twitter such as hashtags and retweets is visualized. The visualization tool will also enable the reflection of the social network for targeted users and their followings and followers.
References
- BusinessofApp. [Online]. Available: https://www.businessofapps.com/data/twitter-statistics/. [Accessed: 13 June 2023].
- V. Wisdom, An Introduction to Twitter Data Analysis in Python, 21 September 2016. [Online]. Available: [Accessed: 22 06 2023] DOI: 10.13140/RG.2.2.12803.30243.
- G. Göktürk, Analysis of Twitter to Identify Trends and Influentials with a Case Study on Turkish Twitter Users, 2014.
- M. H. T. G. E. Karadağ, Spor Taraftarlarının Twitter Kullanım Alışkanlıklarının İncelenmesi: Fırat Üniversitesi Örneği, Spor Eğitim Dergisi, Vol. 3, no. 1, pp. 44-53, 2019.
- P. Brassier, From Korea to the World: Women’s Role as Peer-leaders in K-pop Transnational Online Brand Communities, Asia Pacific Business Review, 2023.
- D. Ediger, K. Jiang, J. Riedy, D. A. Bader, C. Corley, R. Farber ve W. N. Reynolds, Massive Social Network Analysis:Mining Twitter for Social Good, 39th International Conference on Parallel Processing, 2010.
- Y. Kanbur, The Use of Twitter as a Research Medium: An Example of an Application on Political Outlook, 2019.
- T. Terpstra, Towards a realtime Twitter analysis during crises for operational crisis management, Proceedings of the 9th International ISCRAM Conference, Vancouver, Canada, April 2012.
- P. P. Alexander Pak, Twitter as a Corpus for Sentiment Analysis and Opinion Mining, Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), 2010.
- A. Kosorukoff, Social Network Analysis Theory and Applications, Passmore D. L., 2011.
Details
| Primary Language | English |
|---|---|
| Subjects | Data Analysis |
| Journal Section | Research Article |
| Authors | |
| Publication Date | February 2, 2024 |
| Published in Issue | Year 2023 Volume: 1 Issue: 1 |
