Abstract
Twitter is growing as a social network, which provides valuable information to understand users’ political tendency. This paper tackles the challenge of providing a streaming thermometer in a context characterized by the presence of multiple political parties. The strategy presented, named Users Interaction Analysis (UIAS), is deployed in a Big-Data environment to manage huge data volumes. Interactions between users are identified and analyzed by means of a Storm framework. Therefore, the system computes an affinity rate among each user and each different political party. From these individual rates a global tendency is obtained. The experimental results presented in this paper reveal that UIAS offers an accurate estimation, achieving a difference of 3.5 points on average compared with the Spanish Elections results on April 2019.
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Notes
- 1.
- 2.
The Twitter API platform provides three tiers for searching Tweets, https://dev.twitter.com/.
- 3.
The center of psychologies researches of the Spanish Goverment http://www.cis.es/cis/opencms/ES/index.html.
- 4.
Macrobarometer March 2019 pre-election http://www.cis.es/cis/export/sites/default/-Archivos/Marginales/3240_3259/3242/es3242mar.pdf.
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Solé, M., Giné, F., Valls, M. (2022). How Twitter Interactions Leak Political Trends. In: Arai, K. (eds) Intelligent Computing. Lecture Notes in Networks and Systems, vol 283. Springer, Cham. https://doi.org/10.1007/978-3-030-80119-9_37
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