Digital Mixed Content Analysis for the Study of Digital Platform Social Data: An Illustration from the Analysis of COVID-19 Risk Perception in the Italian Twittersphere

Abstract

The explosion of platform social data as digital secondary data, collectable through sophisticated and automatized query systems or algorithms, makes it possible to accumulate huge amounts of dense and miscellaneous data. The challenge for social researchers becomes how to extract meaning and not only trends in a quantitative and in a qualitative manner. Through the application of a digital mixed content analysis design, we present the potentiality of a hybrid digitalized approach to social content applied to a very tricky question: the recognition of risk perception during the first phase of COVID-19 in the Italian Twittersphere. The contribution of our article to mixed methods research consists in the extension of the existing definitions of content analysis as a mixed approach by combining hermeneutic and automated procedures, and by creating a design model with vast application potential, especially when applied to the digital scenario.

Keywords

digital mixed content analysis design digital platform social data COVID-19 pandemic Italy Twitter

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Puwar

(2012). A manifesto for live methods: Provocations and capacities. The Sociological Review, 60(1_suppl), 6–17. https://doi.org/10.1111/j.1467-954x.2012.02114.x

Beck

P. U.

(1992). Risk society: Towards a new modernity. Sage.

Beer

(2014). Punk sociology. Palgrave.

Benzécri

J. P.

(1973). L’analyse des données. Dunod.

Berelson

(1952). Content analysis in communication research. Free Press.

Bergman

M. M.

(2010). Hermeneutic content analysis: Textual and audiovisual analyses within a mixed methods framework. In Tashakkori

Teddlie

(Eds.), SAGE handbook of mixed methods in social & behavioral research (2nd ed., pp. 379–396). Sage.

Blei

D. M.

A. Y.

Jordan

M. I.

(2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3(2003), 993–1022.

Bryman

(2012). Social research methods (4th ed.). Oxford University Press.

Caliandro

Gandini

(2016). Qualitative research in digital environments: A research toolkit. Routledge.

10.

Carley

(1990). Content analysis. In Asher

R. E.

(Ed.), The encyclopedia of language and linguistics (pp. 725–730). Pergamon.

11.

Cole

F. L.

(1988). Content analysis: Process and application. Clinical Nurse Specialist, 2(1), 53–57. https://doi.org/10.1097/00002800-198800210-00025

12.

Creswell

J. W.

(1999). Mixed-method research: Introduction and application. In Cizek

G. J.

(Ed.), Handbook of educational policy (pp. 455–472). Academic.

13.

Creswell

J. W.

Plano Clark

V. L.

(2017). Designing and conducting mixed methods research (3rd ed.). Sage.

14.

Decreto del Presidente del Consiglio dei Ministri [DPCM] . (2020, March 8). Ulteriori disposizioni attuative del decreto-legge 23 febbraio 2020, n. 6, recante misure urgenti in materia di contenimento e gestione dell’emergenza epidemiologica da COVID-19, (20°01522) (GU Serie Generale n.59 del 08-03-2020). https://www.gazzettaufficiale.it/eli/id/2020/03/08/20A01522/sg

15.

Global Digital Report . (2020). Datareportal. https://datareportal.com/reports/digital-2020-global-digital-overview

16.

Governo Italiano Presidenza del Consiglio dei Ministri [GIPCM] , (2020, March 9). Decreto iorestoacasa. https://www.governo.it/it/articolo/firmato-il-dpcm-9-marzo-2020/14276

17.

Hamad

E. O.

Savundranayagam

M. Y.

Holmes

J. D.

Kinsella

E. A.

Johnson

A. M.

(2016). Toward a mixed-methods research approach to content analysis in the digital age: The combined content-analysis model and its applications to health care Twitter feeds. Journal of Medical Internet Research, 18(3), Article e60. https://doi.org/10.2196/jmir.5391

18.

Hernandez-Suarez

Sanchez-Perez

Toscano-Medina

Martinez-Hernandez

Sanchez

Perez-Meana

(2018). A web scraping methodology for bypassing twitter API restrictions. arXiv preprint arXiv:1803.09875

19.

Herring

S. C.

(2009). Web content analysis: Expanding the paradigm. In J. Hunsinger (ed.) International Handbook of Internet Research, Netherlands: Springer, 233–249. https://doi.org/10.1007/978-1-4020-9789-8_14

20.

Hesse-Biber

Johnson

R. B.

(2013). Coming at things differently: Future directions of possible engagement with mixed methods research. Journal of Mixed Methods Research, 7(2), 103–109. https://doi.org/10.1177/1558689813483987

21.

Hine

(2005). Virtual methods: Issues in social research on the Internet. Berg Publisher.

22.

Holsti

O. R.

(1969). Content analysis for the social sciences and humanities. Addison-Wesley.

23.

Hsieh

Shannon

S. E.

(2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687

24.

Jelodar

Wang

Yuan

Feng

Jiang

Zhao

(2019). Latent Dirichlet allocation (LDA) and topic modeling: Models, applications, a survey. Multimedia Tools and Applications, 78(11), 15169–15211. https://doi.org/10.1007/s11042-018-6894-4

25.

Keyes

K. M.

Westreich

(2019). UK Biobank, big data, and the consequences of non-representativeness. Lancet, 393(10178), 1297. https://doi.org/10.1016/s0140-6736(18)33067-8

26.

Kitchin

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

27.

Krippendorff

(2018). Content analysis: An introduction to its methodology (4th ed.). Sage.

28.

Lasswell

H. D.

Leites

Fadner

Goldsen

J. M.

Grey

Janis

I. L.

(1949). The language of politics. Studies in quantitative semantics. George Stewart.

29.

Lebart

(1994). Complementary use of correspondence analysis and cluster analysis. In Greenacre

M. J.

Blasius

(Eds.), Correspondence analysis in the social sciences (pp. 162–178). Academic.

30.

Lebart

Salem

Berry

(1998). Exploring textual data. Springer Science & Business Media.

31.

Leetaru

(2019, March 7). How data scientists turned against statistics. Forbes. https://www.forbes.com/sites/kalevleetaru/2019/03/07/how-data-scientists-turned-against-statistics/?sh=3d53666257c8

32.

Lewis

S. C.

Zamith

Hermida

(2013). Content analysis in an era of big data: A hybrid approach to computational and manual methods. Journal of Broadcasting & Electronic Media, 57(1), 34–52. https://doi.org/10.1080/08838151.2012.761702

33.

Lupton

(2014). Digital sociology. Routledge.

34.

Marres

(2017). Digital sociology: The reinvention of social research. John Wiley & Sons.

35.

Orina

W. A.

Mwangi

G. F.

Sitati

R. N.

Nyabola

(2015). Content analysis and a critical review of the exploratory design. General Education Journal, 4(2), 32–45.

36.

Renn

(1992). Risk communication: Towards a rational discourse with the public. Journal of Hazardous Materials, 29(3), 465–519. https://doi.org/10.1016/0304-3894(92)85047-5

37.

Riff

Lacy

Fico

Watson

(2019). Analyzing media messages: Using quantitative content analysis in research (4th ed.). Routledge.

38.

Rogers

(2009). The end of the virtual: Digital methods. Amsterdam University Press.

39.

Rogers

(2013). Digital methods. MIT Press.

40.

Schreier

(2012). Qualitative content analysis in practice. Sage.

41.

Schreier

(2013). Qualitative content analysis. In E. Flick (Ed.), The Sage handbook of qualitative data analysis (pp.170–183). Sage.

42.

Snelson

C. L.

(2016). Qualitative and mixed methods social media research: A review of the literature. International Journal of Qualitative Methods, 15(1), 1–15. https://doi.org/10.1177/1609406915624574

43.

Teddlie

Tashakkori

(2011). Mixed methods research: Contemporary issues in an emerging field. In Denzin

N. K.

Lincoln

Y. S.

(Eds.), Handbook of qualitative research (4th ed., pp. 285–300). Sage.

44.

Vaezi

Javanmard

S. H.

(2020). Infodemic and risk communication in the era of CoV-19. Advanced Biomedical Research, 9(1), 10. https://doi.org/10.4103/abr.abr_47_20

45.

Zeng

(2012). A topic modeling toolbox using belief propagation. The Journal of Machine Learning Research, 13(1), 2233–2236.