A Mixed Content Analysis Design in the Study of the Italian Perception of the Covid-19 on Twitter

The digital era and the explosion of social, user-generated and freely available and usable content on the net has brought to the fore a classic technique, too often accused of being highly subjective and with a high consumption of human intellectual workforce. This is the Content Analysis which has seen an unprecedented explosion in recent years. In addition to the incessant flow, speed of diffusion and high volume of today's big data, which require us to ask ourselves about covered, the attention of social researchers – as well as of anyone interested in drawing information from this enormous proliferation of data – is shifted to the possibility of having a notion of the contents conveyed, of the sentiment expressed, of the polarities that are realized, and of many other information that indirectly speak of tastes, opinions, beliefs and transformations that run the behaviour of the users of the Net. In fact, secondary data available on the Net, collectable through sophisticated query systems with API or with web scraping software, make it possible to accumulate huge amounts of this social and dense data, from which it is possible to try to extract, not only trends, but real knowledge. This is how new applications, new software, new algorithms are developed, which allow the extraction of this knowledge nested into digital data. All the peculiarities that have characterized the Content Analysis in its qualitative (Shreier, 2012) and quantitative (from the dawn, Berelson, 1952, to the present day, Riff et al., 2019) versions, the contaminations with text mining techniques and the continuous interconnections with network analysis techniques, are recovered. This brings to the attention of the social researcher the continuous evolution of the cognitive horizon which allows to access this new digital frontier of Content Analysis, a frontier that has led to the breaking down of the boundaries between qualitative and quantitative and to the birth of pushed hybridizations, both with and between methods. This enriches the value of the results that can be produced with the Content Analysis and limits, until disappearing, all the critical horizons that have classically left this technique in the shade, allowing it to find new applicative dignity, validity and reliability (Hamad, 2016). In order to explain this evidence, the contribution that we will present will review some recent studies based on Content Analysis, digital data and integrated methods, trying to prove that the return to attention of Content Analysis techniques is not only due to the change in the scenario and in the data analysed, but to the ability of this technique to innovate and evolve itself, leading to open analytical perspectives beyond contingent changes.