Social Sciences Research Methods Regarding COVID-19 Pandemic. A PRISMA Systematic Review.


  • Ciro Clemente De Falco University of Naples Federico II, Italy
  • Emilia Romeo University of Salerno, Italy


covid-19, Digital/digitized methods, Sistematic Literature Review, SLR, Big data


In the digital society, the traditional methods of social research for the study of society have been accompanied by innovative methodological proposals: digital and digitized methods , which are now applied to many themes. In 2020 the most debated topic was certainly the one concerning the Covid-19 pandemic; a “total social fact” of which not only the medical aspects have been analyzed, a substantial scientific production, indeed, has concerned the impacts that the pandemic itself and the measures that governments have taken to resist it has had on society. Starting from these considerations, the aim of this work is to offer an overview of the topics analyzed and the research methods used to investigate this disruptive event in academic research concerning the social sciences - and in particular that which focused on the Italian case - during the last year. To map the state of the art, consolidate the heterogeneous corpus of knowledge, and investigate the different methodological approaches used (tradition/digital/digitized) a methodological approach was applied based on a systematic review of the literature conducted with the PRISMA method and carried out with a third type content analysis.


Aiello F., Bonanno G. & Foglia F. (2020). On the choice of accommodation type at the time of Covid-19. Some evidence from the Italian tourism sector, Current Issues in Tourism.

Amaturo E. (2012). Metodologia della ricerca sociale, Utet

Aquilanti, L., Gallegati, S., Temperini, V., Ferrante, L., Skrami, E., Procaccini, M., & Rap-pelli, G. (2020). Italian Response to Coronavirus Pandemic in Dental Care Access: The DeCADEStudy.International journal of environmental research and public health, 17(19), 6977.

Badell-Grau, R. A., Cuff, J. P., Kelly, B. P., Waller-Evans, H., & Lloyd-Evans, E. (2020). Investigating the Prevalence of Reactive Online Searching in the COVID-19 Pandemic: Infoveillance Study. Journal of medical Internet research, 22(10), e19791.

Boccia Artieri, G.(2015). Gli effetti sociali del web. Forme della comunicazione e metodo-logie della ricerca online. Milano, Italia: Franco Angeli.

Bonaccorsi, G., Pierri, F., Cinelli, M., Flori, A., Galeazzi, A., Porcelli, F.,Pammolli, F. (2020). Economic and social consequences of human mobility restrictions under COVID-19. Proceedings of the National Academy of Sciences, 117(27), 15530-15535.

Borges J., Hain H., Sudrich S., & Beigl M. (2017). "Event detection for smarter cities," 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (Smart-World/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1-8.

Briscese G., Lacetera N., Macis M., & Tonin M. (2020). Compliance with COVID-19 So-cial-Distancing Measures in Italy: The Role of Expectations and Duration. Iza Discus-sion Paper No.13092, available at SSRN:

Caliandro, A., & Gandini, A. (2016). Qualitative research in digital environments: A re-search toolkit. Routledge.

Capone, V., Caso, D., Donizzetti, A. R., & Procentese, F. (2020). University student mental well-being during COVID-19 outbreak: What are the relationships between information seeking, perceived risk and personal resources related to the academic context? Sustainability, 12(17), 7039.

Carrieri V, Madio L, & Principe F. (2019). Vaccine hesitancy and (fake) news: quasi-experimental evidence from Italy. Health Econ 2019 Nov; 28(11):1377-1382.

Chatfield, A. T., & Brajawidagda, U. (2013). Twitter early tsunami warning system: A case study in Indonesia's natural disaster management. In 2013 46th Hawaii international conference on system sciences (pp. 2050-2060). IEEE. 10.1109/HICSS.2013.579

Chen, X., Elmes, G., Ye, X., & Chang, J. (2016). Implementing a real-time Twitter-based system for resource dispatch in disaster management. GeoJournal, 81(6), 863-873.

Cusinato, M., Iannattone, S., Spoto, A., Poli, M., Moretti, C., Gatta, M., &Miscioscia, M. (2020). Stress, Resilience, and Well-Being in Italian Children and Their Parents during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 17(22). 8297.

De Santis, E., Martino, A., & Rizzi, A. (2020). An Infoveillance System for Detecting and Tracking Relevant Topics From Italian Tweets During the COVID-19 Event. IEEE Access, 8, 132527-132538. 10.1109/ACCESS.2020.3010033

Elias, P. (2012). Big data and the social sciences: a perspective from the ESRC, presenta-tion at the conference Shaping society.

Emani, C. K., Cullot, N., & Nicolle, C. (2015). Understandable big data: a survey. Computer science review, 17, 70-81.

Falcone, R., & Sapienza, A. (2020). How COVID-19 Changed the Information Needs of Italian Citizens. International Journal of Environmental Research and Public Health, 17(19), 6988.

Gaggi, O., Kolasinska, A. B., Mirri, S., &Prandi, C. (2020). The new classmate: an explora-tion of how CoVid-19 affected primary schools activities in Italy. In Proceedings of the 6th EAI International Conference on Smart Objects and Technologies for Social Good, 36-41,

Germani, A.; Buratta, L.; Delvecchio, E.; Mazzeschi, C. (2020). Emerging Adults and COVID-19: The Role of Individualism-Collectivism on Perceived Risks and Psycholog-ical Maladjustment. Int. J. Environ. Res. Public Health 2020, 17, 3497.

Graffigna, G., Bosio, C., Savarese, M., Barello, M., & Barello, S. (2020). “# I-Am-Engaged”: Conceptualization and First Implementation of a Multi-Actor Participatory, Co-designed Social Media Campaign to Raise Italians Citizens’ Engagement in Pre-venting the Spread of COVID-19 Virus. Frontiers in psychology, 11, 2428.

Halford, S., Pope, C., & Weal, M. (2013). Digital futures? Sociological challenges and op-portunities in the emergent semantic web. Sociology, 47(1), 173-189.

Hampton, K. N. (2017). Studying the digital: Directions and challenges for digital methods. Annual Review of Sociology, 43, 167-188.

Iacuzzi, S., Fedele, P., & Garlatti, A. (2020). Beyond Coronavirus: the role for knowledge management in schools responses to crisis. Knowledge Management Research & Prac-tice, 1-6.

Kitchin, R. (2014). The data revolution: Big data, open data, data infrastructures and their consequences. New York: Sage

Krippendorff, K. (2004). Reliability in content analysis. Human communication research, 30(3), 411-433.

Krippendorff, K. (2018). Content analysis: An introduction to its methodology. New York: Sage publications.

Lakatos, I. (1970). History of science and its rational reconstructions. In PSA: Proceedings of the biennial meeting of the philosophy of science association (Vol. 1970, pp. 91-136). D. Reidel Publishing.

Lenzo, V., Quattropani, M. C., Musetti, A., Zenesini, C., Freda, M. F., Lemmo, D., ... &Cattivelli, R. (2020). Resilience contributes to low emotional impact of the COVID-19 outbreak among the general population in Italy. Frontiers in Psychology, 11.

López Fernández, M. C., Serrano Bedia, A. M., & Pérez Pérez, M. (2016). Entrepreneurship and family firm research: A bibliometric analysis of an emerging field. Journal of Small Business Management, 54(2), 622-639.

Losito, G. (1996). L’analisi del contenuto nella ricerca sociale (Vol. 1). Milano: FrancoAn-geli.

Lupton D. (2015), Digital sociology, London, Routledge.

Mahrt, M., & Scharkow, M. (2013). The value of big data in digital media re-search. Journal of Broadcasting & Electronic Media, 57(1), 20-33.

Manesh, M. F., Pellegrini, M. M., Marzi, G., & Dabic, M. (2020). Knowledge management in the fourth industrial revolution: Mapping the literature and scoping future avenues. IEEE Transactions on Engineering Management, 68(1), 289-300.

Manovich, L. (2012). Trending: The Promises and the Challenges of Big Social Data. In Gold M. (Ed.), Debates in the Digital Humanities (pp. 460-475). Minneapolis; London: University of Minnesota Press.

Marres, N. (2012). The redistribution of methods: On intervention in digital social research, broadly conceived. The Sociological Review, 60, 139165.

Mauss M. (2002). Saggio sul dono. Torino: Einaudi.

Mellin J., & Berndtsson M. (2009). Event Detection. In: LIU L., ÖZSU M.T. (eds) En-cyclopedia of Database Systems. Springer, Boston, MA.

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of internal medicine, 151(4), 264-269.

Moscadelli, A., Albora, G., Biamonte, M. A., Giorgetti, D., Innocenzio, M., Paoli, S., ... &Bonaccorsi, G. (2020). Fake news and Covid-19 in Italy: Results of a quantitative ob-servational study. International Journal of Environmental Research and Public Health, 17(16), 5850.

Pellegrini, M., Ponzo, V., Rosato, R., Scumaci, E., Goitre, I., Benso, A., ... &Broglio, F. (2020). Changes in weight and nutritional habits in adults with obesity during the “lockdown” period caused by the COVID-19 virus emergency. Nutrients, 12(7), 2016.

Pitrelli, N. (2017). Big data e metodi digitali per la ricerca in comunicazione della scienza: opportunità, sfide e limiti. JCOM, 16 (02), C01_it.

Pohl, D., Bouchachia, A., & Hellwagner, H. (2012). Automatic sub-event detection in emergency management using social media. In Proceedings of the 21st international conference on world wide web (pp. 683-686).

Procentese, F., Capone, V., Caso, D., Donizzetti, A. R., & Gatti, F. (2020). Academic Community in the Face of Emergency Situations: Sense of Responsible Togetherness and Sense of Belonging as Protective Factors against Academic Stress during COVID-19 Outbreak. Sustainability, 12(22), 9718.

Rahman, M., Thill, J. C., & Paul, K. C. (2020). COVID-19 pandemic severity, lockdown regimes, and people’s mobility: Early evidence from 88 coun-tries. Sustainability, 12(21), 9101.

Rice R. (1990). Computer-mediated communication system network data. Int. J. Man-Mach. Stud., 32 (6), 627–647.

Robinson, P., & Lowe, J. (2015). Literature reviews vs systematic reviews. Australian and New Zealand journal of public health, 39(2), 103-103.

Rogers, R. (2009). The end of the virtual: Digital methods (Vol. 339). Amsterdam University Press.

Rogers R (2013). Metodi digitali: fare ricerca sociale con il web. Bologna: Il Mulino.

Rolandi, E., Vaccaro, R., Abbondanza, S., Casanova, G., Pettinato, L., Colombo, M., & Guaita, A. (2020). Loneliness and social engagement in older adults based in Lombardy during the COVID-19 lockdown: The long-term effects of a course on social networking sites use. International journal of environmental research and public health, 17(21), 7912.

Roma, P., Monaro, M., Colasanti, M., Ricci, E., Biondi, S., Di Domenico, A., ... & Mazza, C. (2020). A 2-Month Follow-Up Study of Psychological Distress among Italian People during the COVID-19 Lockdown. International Journal of Environmental Research and Public Health, 17(21), 8180.

Rositi, F. (1988). Analisi del contenuto. La ricerca sull’industria culturale, 59-94.

Ruiz-Roso, M. B., de CarvalhoPadilha, P., Mantilla-Escalante, D. C., Ulloa, N., Brun, P., Acevedo-Correa, D., ... & Carrasco-Marín, F. (2020). Covid-19 confinement and changes of adolescent’s dietary trends in Italy, Spain, Chile, Colombia and Bra-zil. Nutrients, 12(6), 1807.

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evi-dence-informed management knowledge by means of systematic review. British journal of management, 14(3), 207-222.

Troise, C., O’Driscoll, A., Tani, M., & Prisco, A. (2020). Online food delivery services and behavioural intention–a test of an integrated TAM and TPB framework. British Food Journal.

Van Eck, N. J. V., &Waltman, L. (2009). How to normalize cooccurrence data? An analy-sis of some well?known similarity measures. Journal of the American society for in-formation science and technology, 60(8), 1635-1651.

Van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using Cit-NetExplorer and VOSviewer. Scientometrics, 111(2), 1053-1070.

Wang, H., Hovy, E., & Dredze, M. (2015). The hurricane sandy twitter corpus. In Workshops at the twenty-ninth AAAI conference on artificial intelligence.