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Shruti Tewari

Researcher at Indian Institute of Management Indore

Publications -  26
Citations -  730

Shruti Tewari is an academic researcher from Indian Institute of Management Indore. The author has contributed to research in topics: Social identity theory & Medicine. The author has an hindex of 10, co-authored 19 publications receiving 464 citations. Previous affiliations of Shruti Tewari include Allahabad University & Indian Institute of Management Ahmedabad.

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How Collective Participation Impacts Social Identity : A Longitudinal Study from India

TL;DR: In this article, a longitudinal questionnaire study conducted at one of the world's largest collective events (the Magh Mela) showed that participants who participated exhibited heightened social identification as a Hindu and increased frequency of prayer rituals.
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A calming cacophony: Social identity can shape the experience of loud noise

TL;DR: In this paper, the authors study the aural experience of a religious festival in North India which is characterized by loud, continuous and cacophonous noise and show that loud noise is experienced as pleasant or unpleasant according to the meanings attributed to it.
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Efficacy and well-being in rural north India: The role of social identification with a large-scale community identity.

TL;DR: Social identification as a Hindu had positive and indirect associations with three measures of well-being through the belief that one can cope with everyday stressors and the application of social psychological theory developed in the urban West to rural north India is discussed.
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Social relations in crowds : recognition, validation and solidarity

TL;DR: In this article, the authors investigated the social-relational changes within a crowd and how these impact collective experience positively, using interviews with participants attending the annual Magh Mela pilgrimage in India.
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Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Tomislav Pavlović, +227 more
- 01 Jul 2022 - 
TL;DR: This paper applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic.