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Is there Lingua Franca in informal scientific communication? Evidence from language distribution of scientific tweets

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  • Yu, Houqiang
  • Xu, Shenmeng
  • Xiao, Tingting

Abstract

Language distribution in scientific communication reflects the influence of different languages on science in global perspective. The study, based on over 450 thousand scientific tweets of all publications indexed by Scopus in June 2015, reveals the language distribution in informal scientific communication. Moreover, this result is compared with the language distribution in formal scientific communication reflected in scientific publications. Results show: (1) The language of scientific tweets is concentrated in English (91%), Japanese (2.4%) and Spanish (1.7%), while the language of scientific publications is concentrated in English (90.6%), Chinese (5%) and German (1.1%). (2) Both scientific tweets and scientific publications present disciplinary differences in language distribution, reflecting the different amount of attention that authors of different languages have on certain disciplines. (3) Except Saudi Arabia, investigated countries all over the world, regardless of whether their native language is English or not, all have English scientific tweets in the dominant position. For the vast majority of these countries, the native language scientific tweets only rank the second position. (4) Overall, 26% of tweeters use more than one language to tweet scientific products, while 49% of scientific tweeters tweet everything in English only. The results indicate that English has undoubtedly become the lingua franca in informal scientific communication.

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  • Yu, Houqiang & Xu, Shenmeng & Xiao, Tingting, 2018. "Is there Lingua Franca in informal scientific communication? Evidence from language distribution of scientific tweets," Journal of Informetrics, Elsevier, vol. 12(3), pages 605-617.
    • Handle: RePEc:eee:infome:v:12:y:2018:i:3:p:605-617
    DOI: 10.1016/j.joi.2018.06.003
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    2. Houqiang Yu & Yue Wang & Shah Hussain & Haoyang Song, 2023. "Towards a better understanding of Facebook Altmetrics in LIS field: assessing the characteristics of involved paper, user and post," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3147-3170, May.

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