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From neuroscience to computer science: a topical approach on Twitter

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Abstract

Twitter is perhaps the most influential microblogging service, with 271 million regular users producing approximately 500 million tweets per day. Previous studies of tweets discussing scientific topics are limited to local surveys or may not be representative geographically. This indicates a need to harvest and analyse tweets with the aim of understanding the level of dissemination of science related topics worldwide. In this study, we use Twitter as case of study and explore the hypothesis of science popularization via the social stream. We present and discuss tweets related to popular science around the world using eleven keywords. We analyze a sample of 306,163 tweets posted by 91,557 users with the aim of identifying tweets and those categories formed around temporally similar topics. We systematically examined the data to track and analyze the online activity around users tweeting about popular science. In addition, we identify locations of high Twitter activity that occur in several places around the world. We also examine which sources (mobile devices, apps, and other social networks) are used to share popular science related links. Furthermore, this study provides insights into the geographic density of popular science tweets worldwide. We show that emergent topics related to popular science are important because they could help to explore how science becomes of public interest. The study also offers some important insights for studying the type of scientific content that users are more likely to tweet.

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Acknowledgements

This research has been supported in part by “Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica” (Grant no. PAPIIT IA301016). Carlos Adolfo Piña-García was partially supported by SNI membership 69310. Carlos Gershenson was partially supported by SNI membership 47907. J. Mario Siqueiros-García was partially supported by SNI membership 54027. We also aknowledge the support of projects 212802, 221341, 260021 and 222220 of CONACyT.

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Authors and Affiliations

  1. Centro de Estudios de Opinión y Análisis, Laboratorio para el Análisis de Información Generada a través de las Redes Sociales en Internet (LARSI), Universidad Veracruzana, Xalapa, Veracruz, Mexico

    C. A. Piña-García

  2. Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas Departamento de Ciencias de la Computación, Universidad Nacional Autónoma de México, Ciudad de México, Mexico

    C. A. Piña-García, J. Mario Siqueiros-García, E. Robles-Belmont, Gustavo Carreón & Carlos Gershenson

  3. Imperial College London, London, UK

    Julio Amador Díaz López

  4. Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Ciudad de México, Mexico

    Carlos Gershenson

  5. SENSEable City Lab, Massachusetts Institute of Technology, Cambridge, MA, USA

    Carlos Gershenson

  6. ITMO University, Birzhevaya liniya 4, St. Petersburg, Russian Federation

    Carlos Gershenson

Authors
  1. C. A. Piña-García
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  2. J. Mario Siqueiros-García
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  3. E. Robles-Belmont
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  4. Gustavo Carreón
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  5. Carlos Gershenson
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  6. Julio Amador Díaz López
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Corresponding author

Correspondence to C. A. Piña-García.

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Piña-García, C.A., Siqueiros-García, J.M., Robles-Belmont, E. et al. From neuroscience to computer science: a topical approach on Twitter. J Comput Soc Sc 1, 187–208 (2018). https://doi.org/10.1007/s42001-017-0002-9

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  • DOI: https://doi.org/10.1007/s42001-017-0002-9

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