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Technology enabled communication during COVID 19: analysis of tweets from top ten Indian IT companies using NVIVO.
Chawla, Swati; Sareen, Puja; Gupta, Sangeeta; Joshi, Meha; Bajaj, Ritu.
  • Chawla S; Noida, Uttar Pradesh India Amity Business School, Amity University.
  • Sareen P; Noida, Uttar Pradesh India Amity Business School, Amity University.
  • Gupta S; Management Education and Research Institute, New Delhi, India.
  • Joshi M; New Delhi, India Delhi School of Management, Delhi Technological University.
  • Bajaj R; Meerpur, Haryana India Indira Gandhi University.
Int J Inf Technol ; 15(4): 2063-2075, 2023.
Article in English | MEDLINE | ID: covidwho-2293214
ABSTRACT
The corona virus (COVID-19) pandemic has impacted industries across the globe. Lockdown was imposed to curb the spread of the deadly virus. This resulted in closure of the factories and manufacturing units. Few sectors switched to work from home (WFH) for the first time. The present study aims to understand and analyze the way in which Information Technology (IT) sector communicated on Twitter during the pandemic. The top ten IT companies in India were selected on the basis of net sales. Qualitative data analysis was employed to extract tweets, understand and analyze them. Tweets were extracted from the official Twitter handles of these top ten IT companies using N-Capture extension tool of NVivo 12 software from April 1, 2020 to April 30, 2021. To get insights out of collected data, Word Cloud, TreeMap and Sentiment Analysis of tweets were carried out using NVivo 12 software. The research found that IT companies focussed on digital transformation, business development, customer satisfaction and enriching customer experience, new product development for healthcare and insurance and organizational resilience. They also focussed on effective communication through Twitter in times of crisis. Most of the companies tweeted moderately positive. Very small numbers of tweets were found to be very negative.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research Language: English Journal: Int J Inf Technol Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Qualitative research Language: English Journal: Int J Inf Technol Year: 2023 Document Type: Article