Unfortunately, the Covid-19 pandemic has been with us now for more than a year and it is likely to remain in some form for many months to come. Researchers haven’t wasted anytime in looking into the impacts of the pandemic on many, many fields including health care, mental health, the news media, social media, education, suicide, purchasing, and the economy, to name a few. We performed a quick literature review of the articles that have been written related to Covid-19 using a text analysis software: QDA Miner and Wordstat. The search wasn’t exhaustive, but by going through google scholar we turned up more than 20 papers published in 2020 that relate to some type of impact from Covid-19. We have listed them at the end of this Blog. There are surely many more to come in 2021. Researchers looked at news articles, social media, surveys, interviews, and other data to assess and measure the effects of the pandemic on different subjects. Here are a few examples we have pulled from the published papers about different data and collection methods they used to analyze the impact of Covid 19 in a particular field.
In their paper Barnes, Diaz, and Arnaboldi (2020) collected 24,153 Twitter over 14 days from users in Italy. They analyzed the data around two government announcements and to see how the study of social media can be an early warning of potential demand issues.
While maybe not surprising given the United States’ multiple failures to control the virus, Sacerdote, Sehgal, and Cook (2020) analyzed media articles and their research showed, “ninety-one percent of stories by U.S. major media outlets are negative in tone versus fifty-four percent for non-U.S. major sources and sixty-five percent for scientific journals. The negativity of the U.S. major media is notable even in areas with positive scientific developments including school re-openings and vaccine trials. Media negativity is unresponsive to changing trends in new COVID-19 cases or the political leanings of the audience. U.S. major media readers strongly prefer negative stories about COVID-19 and negative stories in general.”
In another media analysis, Hossain (2020) used QDA Miner Lite to analyze articles in newspapers and the popular press, blog posts, and video clips to see the effect of the pandemic on the sharing economy. The paper explores the obvious downsides such as fear, anxiety, job losses, salary cuts but also discusses how the pandemic might have some lasting changes on the industry.
In their paper, Ojo and Onwuegbuzie (2020) examined the impact of Covid 19 and the switch to virtual learning on students. They sent a questionnaire to all students at the University of the Witwatersrandits in South Africa and received more than 4,000 responses representing more than 10% of the student population. There were both Likert scale and open-ended questions. The authors used WordStat to perform topic modeling on the open-ended responses. The study raised some important issues about South African, bringing back some painful elements from the past and outlined challenges for the future for online learning.
Other Covid related papers such as Kim, Qian, and Aslam (2020) and Kumar, Nedungalaparambil, and Mohanan (2020) used QDA Miner to perform literature reviews assessing Covid’s impact in different areas of health care. Zorikhina, et al. (2020) and Al-Rawi, Shukla, (2020) used QDA Miner and WordStat to analyze large numbers of tweets and other social media. To find out more about how to import and analyze social media with Provalis software please read this white paper.
News articles are clearly an important source for information about Covid-19, its affects and people’s reactions to the various measures being used by health agencies and governments to combat the pandemic. Daum et al. (2020) used QDA Miner to analyze news articles. Four additional papers used QDA Miner Lite to analyze news articles (Balaji & Patel, 2020; Birner et al., 2020;, Atabekova, 2020; Eriksson & Stenius, 2020).
All the analysis was not limited to text, Sadasri (2020) used QDA Miner to analyze images and Instagram postings related to celebrities and Covid. Tourism has taken a huge hit during the pandemic and two papers (Uğur & Akbıyık, 2020; Buhalis & Moldavska, 2021) use Provalis software to help them explore some of the impact on the tourism industry. Wang, and Cruz (2020) used the geotagging features in WordStat to analyze a geotagged twitter dataset of tweets relating to Covid from 150 U.S. colleges. To learn more about how to use the GIS features we have posted a white paper on our website.
Finally, we recently hosted a Lunch & Learn highlighting Covid-19. Dr. Christina Silver, Dr. Eric Wastlund, and Sture Nojd presented their work on Balancing the Insights of Human Interpretation with the Power of Qualitative Software: Analysing COVID-19 Habits using WordStat and QDA Miner. They interviewed people in 25 countries about their habits and how they changed or didn’t change during the pandemic. The webinar also lays out how they designed their research and used the software in their analysis. You can watch a recording of the webinar here.
As we move forward in this pandemic, we see it is affecting all elements of society in ways that were predictable and in ways that were not. Some of the changes such as travel and social gatherings will likely be temporary but in other areas such as education, health care, shared services, and retail, the lessons learned from this time will have long-term implications. Text analytics is already proving to be an invaluable tool in discovering what those changes are and where we should be focussing on additional research.
Al-Rawi, A., & Shukla, V. (2020). Bots as Active News Promoters: A Digital Analysis of COVID-19 Tweets. Information, 11, 461.
Atabekova, A. (2020). University discourse to foster youth’s sustainability in society amidst COVID19: International and Russian Features. Sustainability, 12(18), 7336.
Balaji, M., & Patel, V. (2020). Hunger, fear and isolation: An analysis of media reports of COVID-19 related suicides in India.
Barnes, S. J., Diaz, M., & Arnaboldi, M. (2020). Understanding panic buying during COVID-19: A text analytics approach. Expert Systems with Applications, 114360.
Birner, R., Blaschke, N., Bosch, C., Daum, T., Graf, S., Güttler, D., & Woode, G. (2020). ‘We would rather die from Covid-19 than from hunger-Exploring lockdown stringencies in five African countries.
Buhalis, D., & Moldavska, I. (2021). In-room Voice-Based AI Digital Assistants Transforming On-Site Hotel Services and Guests’ Experiences. In Information and Communication Technologies in Tourism 2021 (pp. 30-44). Springer, Cham.
Daum, T., Birner, R., Biesalski, K., Blaschke, N., Bosch, C., Güttler, D., … & Woode, G. (2020). Between pandemics and famines: Towards nutrition-sensitive lockdowns during Covid-19 and beyond.
Eriksson, N., & Stenius, M. (2020). Changing behavioral patterns in grocery shopping in the initial phase of the COVID-19 crisis—A qualitative study of news articles. Open Journal of Business and Management, 8(05), 1946
Hossain, M. (2020). The effect of the Covid-19 on sharing economy activities. Journal of Cleaner Production, 280, 124782.
Kim, Y. J., Qian, L., & Aslam, M. S. (2020). The impact of substance use disorder on the mental health among COVID-19 patients: A protocol for systematic review and meta-analysis. Medicine, 99(46).
Kumar, R., Nedungalaparambil, N. M., & Mohanan, N. (2020). Emergency and primary care collaboration during COVID-19 pandemic: A quick systematic review of reviews. Journal of Family Medicine and Primary Care, 9(8), 3856.
Ojo, E. O., & Onwuegbuzie, A. J. (2020). University Life in an Era of Disruption of COVID-19: A Meta-Methods and Multi-Mixed Methods Research Study of Perceptions and Attitudes of South African Students. International Journal of Multiple Research Approaches, 12(1).
Sacerdote, B., Sehgal, R., & Cook, M. (2020). Why Is All COVID-19 News Bad News? (No. w28110). National Bureau of Economic Research.
Sadasri, L. M. (2020). Micro-celebrity participation and risk communication in Indonesia. Pacific Journalism Review: Te Koakoa, 26(2), 53-71.
Uğur, N. G., & Akbıyık, A. (2020). Impacts of COVID-19 on global tourism industry: A cross-regional comparison. Tourism Management Perspectives, 36, 100744.
Wang, Z., & Cruz, I. F. (2020, November). Analysis of the Impact of COVID-19 on Education Based on Geotagged Twitter. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Modeling and Understanding the Spread of COVID-19 (pp. 15-23).
Zorikhina Nilsson, N., Mustajoki, A., Tous-Rovirosa, A., Guzman Tirado, R., Dergacheva, D., Vepreva, I., & Itskovich, T. (2020). Covid-19: katastrofa v jazykovom izmerenii raznych stran. Covid-19: A Disaster in the Linguistic Dimension of Different Countries. Quaestio Rossica, 8(4), 1369-1390.