Social Sciences Research Methods Regarding COVID-19 Pandemic. A PRISMA Systematic Review.
Abstract
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.
References
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. https://doi.org/10.1080/13683500.2020.1846504
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.https://doi.org/10.3390/ijerph17196977
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.https://doi.org/10.2196/19791
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. https://doi.org/10.1073/pnas.2007658117
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. https://doi.org/10.1109/UIC-ATC.2017.8397590.
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: https://ssm.com/abstract=3568295
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. https://doi.org/10.3390/su12177039
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. https://doi.org/10.1002/hec.3937
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. https://doi.org/ 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. https://doi.org/10.1007/s10708-016-9745-8
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.https://doi.org/10.3390/ijerph17228297
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. https://doi.org/10.1016/j.cosrev.2015.05.002
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. https://doi.org/10.3390/ijerph17196988
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, https://doi.org/10.1145/3411170.3411239
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. https://doi.org/10.3390/ijerph17103497
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. https://doi.org/10.3389/fpsyg.2020.567101
Halford, S., Pope, C., & Weal, M. (2013). Digital futures? Sociological challenges and op-portunities in the emergent semantic web. Sociology, 47(1), 173-189. https://doi.org/10.1177/0038038512453798
Hampton, K. N. (2017). Studying the digital: Directions and challenges for digital methods. Annual Review of Sociology, 43, 167-188. https://doi.org/10.1177/0038038512453798
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. https://doi.org/10.1080/14778238.2020.1838963
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. https://doi.org/10.3389/fpsyg.2020.576485
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. https://doi.org/10.1111/jsbm.12161
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. https://doi.org/10.1080/08838151.2012.761700
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. https://doi.org/10.1109/TEM.2019.2963489
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.https://doi.org/10.1111/j.1467-954X.2012.02121.x
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. https://doi.org/10.1007/978-0-387-39940-9_506
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. https://doi.org/10.1371/journal.pmed.1000097
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. https://doi.org/10.3390/ijerph17165850
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. https://doi.org/10.3390/nu12072016
Pitrelli, N. (2017). Big data e metodi digitali per la ricerca in comunicazione della scienza: opportunità, sfide e limiti. JCOM, 16 (02), C01_it. https://doi.org/10.22323/2.16020301
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). https://doi.org/10.1145/2187980.2188180
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. https://doi.org/10.3390/su12229718
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. https://doi.org/10.3390/su12219101
Rice R. (1990). Computer-mediated communication system network data. Int. J. Man-Mach. Stud., 32 (6), 627–647. https://doi.org/10.1016/S0020-7373(05)80104-X
Robinson, P., & Lowe, J. (2015). Literature reviews vs systematic reviews. Australian and New Zealand journal of public health, 39(2), 103-103. https://doi.org/10.1111/1753-6405.12393
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. https://doi.org/10.3390/ijerph17217912
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. https://doi.org/10.3390/ijerph17218180
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.https://doi.org/10.3390/nu12061807
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.https://doi.org/10.1111/1467-8551.00375
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.https://doi.org/10.1108/BFJ-05-2020-0418
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. https://doi.org/10.1002/asi.21075
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.