Hypothetical reported speech as pedagogical practice in multilingual classrooms in India

Chandras, Jessica

doi:10.1080/09500782.2021.1981368

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…Although the data is sourced in English, we note that most of India has English as a second language and there are a number of regional languages in India. The 2011 Indian census recorded 31 regional Indian languages (such as Hindi, Bengali, Tamil, and Punjabi) had at least one million speakers each [ 106 ]; this gives a better picture of the language diversity in India which is a major challenge when it comes to language translation systems [ 107 ]. Hence, there would be a bias in expression, with terms that are associated with regional languages according to the Tweet user background.…”

Section: Discussionmentioning

confidence: 99%

Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron

Lande,

Pillay,

Chandra

2023

PLoS ONE

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Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as the COVID-19 pandemic. In this paper, we use prominent deep learning-based language models for COVID-19 topic modelling taking into account data from the emergence (Alpha) to the Omicron variant in India. Our results show that the topics extracted for the subsequent waves had certain overlapping themes such as governance, vaccination, and pandemic management while novel issues aroused in political, social and economic situations during the COVID-19 pandemic. We also find a strong correlation between the major topics with news media prevalent during the respective time period. Hence, our framework has the potential to capture major issues arising during different phases of the COVID-19 pandemic which can be extended to other countries and regions.

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Section: Discussionmentioning

confidence: 99%