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Social, economic, and demographic factors drive the emergence of Hinglish code-mixing on social media

Author

Listed:
  • Ayan Sengupta

    (Indian Institute of Technology Delhi)

  • Soham Das

    (Indraprastha Institute of Information Technology)

  • Md. Shad Akhtar

    (Indraprastha Institute of Information Technology)

  • Tanmoy Chakraborty

    (Indian Institute of Technology Delhi
    Indian Institute of Technology Delhi)

Abstract

The advent of globalization and adaptation to multiple cultures has emanated a fusion of Hindi and English, casually known as Hinglish. The phenomenon of mixing multiple languages (such as Hindi and English) within a single utterance is often called code-mixing. Lately, code-mixed Hinglish has emerged as a dominant conversational language for Hindi-speaking citizens both online (on social media platforms) and offline. Although previous studies investigated such linguistic traits of Hinglish over the past few years, some pertinent questions still need to be answered: How did Hinglish evolve? And, what are the factors behind the evolution of Hinglish? Does the fusion of English impact all Hindi words similarly? To this end, we explore the empirical and statistical shreds of evidence behind the rise of Hinglish on social media such as Twitter. We show that adopting Hinglish depends on several socio-economic and demographic factors. We further formulate dynamic models to explore the socio-economic factors driving the growth of Hinglish, derive the future growth of Hinglish in the upcoming years, and estimate the propensity of users to change their linguistic preferences. Our study highlights that the Hinglish population has evolved steadily between 2014 and 2022, with an annualized growth rate of 1.2%, and the usage of Hinglish on Twitter has increased annually by 2%. Further, we find that the impact of Hinglish evolution is not uniform across different word groups and affects the contextual meaning of different words differently. Although our findings are specific to the Indian Hinglish community, our study can be generalized to understand the evolution and dynamics of other code-mixed languages, such as Spanish-English or Chinese-English.

Suggested Citation

  • Ayan Sengupta & Soham Das & Md. Shad Akhtar & Tanmoy Chakraborty, 2024. "Social, economic, and demographic factors drive the emergence of Hinglish code-mixing on social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03058-6
    DOI: 10.1057/s41599-024-03058-6
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    References listed on IDEAS

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    1. Harini Barath, 2019. "Indian initiatives aim to break science’s language barrier," Nature, Nature, vol. 571(7764), pages 289-290, July.
    2. Daniel M. Abrams & Steven H. Strogatz, 2003. "Modelling the dynamics of language death," Nature, Nature, vol. 424(6951), pages 900-900, August.
    3. Lin-Fei Nie & Zhi-Dong Teng & Juan J. Nieto & Il Hyo Jung, 2013. "Dynamic Analysis of a Two-Language Competitive Model with Control Strategies," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-13, December.
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