The paper demonstrates how an unfamiliar, globally affected social issue like the present pandemic immediately affects languages and results in language variation using the existing framework of cognitive sociolinguistics (Geeraerts, 2005; Geeraerts, Kristiansen & Peirsman, 2010; Zenner, Speelman & Geeraerts, 2010; Labov, 2011; Zenner et al., 2012; Pütz, Robinson & Reif, 2014; Hollmann, 2017). The COVID-19 outbreak has resulted in using many new words and phrases especially, in the daily discourses in English. The universality of the English language and borrowings from English to other languages has become an inevitable process during this period. Similarly, some of the less common words that already existed, in general, gained attention and usage. Language variation is viewed as a gradual, slow and systematic process (Chambers, Trudgill & Schilling, 2013; Labov, 1972; 2001; 2011); the present scenario is diverging by a 'swift variation' as these expressions spread globally as the virus irrespective of the language. Therefore, observing language variations in progress due to a social phenomenon like this gains momentum. Thus, the paper explores the sociocognitive aspects of linguistic adaptations in Indian languages during the pandemic. It obtains evidence of variations in discourses and their semantic adaptations from Indian languages; Dravidian languages namely Malayalam and Tamil; and Indo-Aryan languages namely Hindi and Bengali. The analysis progresses along with the qualitative and quantitative analysis of linguistic additions and borrowings from the pandemic code and their further semantic adaptations. Indian languages also follow the global phenomenon of incorporating a lot of borrowed expressions from English (Devy, 2015). The paper develops on the analysis of the semantic familiarity of the speakers with the corpus created from the pandemic code. The 20 informants for each language are from various age groups ranging from 15 to 85, who cannot understand or speak English beyond the word level. The study employed digital cue cards containing the expressions in their contexts written with the Malayalam writing system. All the possible semantic associations of each item in the corpus made by every speaker were recorded and analysed further. Apart from the apparent assimilations, the factors of analysis include the following: i) familiarity index (which includes checking multiple attributions of an expression), ii) semantic adaptation, iii) other semantic attributions and iv) semantic extensions. The study explains the pandemic linguistic expressions, which are elevated as a 'universal pandemic code', by exploring their impact on the languages under the study. These current variations in these languages were observed to have a similar pattern that creates a 'swift language variation', unlike the previously explored language variations, which had a slow and gradual pace. It further identifies the existence of two categories of expressions based on the discourse patterns; a) Familiar Expressions that are adapted in daily discourses (e.g.: mask, quarantine, containment, lockdown, among others.) and b) Less familiar expressions (pandemic, community spread, flatten the curve, among others) that chiefly present among the older generation than the younger age groups. The more familiar words are observed to be undergoing a semantic extension in the daily discourses. On the other hand, some of the familiar words are observed to be semantically narrowed with one single attribution also. Thus, the study validates that the more familiar expressions in the corpus are observed to be undergoing a semantic extension in the daily discourses. On the other hand, some of the familiar expressions are observed to have semantic narrowing with one single attribution. The paper tries to develop a pattern of 'swift variation' across the languages under analysis and show how a cognitive sociolinguistic analysis helps to theoretically explain a new dichotomy of 'slow' versus 'swift' variations in languages.
