The field of the Digital Humanities has not a very long history, but it has changed significatively since its beginning. Already in 2011, David Berry talked about 3 waves in this emergent area: a first moment of digitalization, when researchers understood technologies as tools to help the management of humanistic resources; a second moment, based on natively digital products, that conceived the tools in their generative mode; finally, Berry intuits a third moment in which the computational revolution would be the motor of the humanistic studies development (Berry, 2011). 

Of course, since 2011 many things have happened, especially talking about knowledge areas affected by technologies and their implementations. For example, around 2015 and next years, Big Data was a very powerful trend, which impacted most of the academic research, including humanities and social sciences. Some years later, around 2017, a turn happened with the consolidation of the term Artificial Intelligence, which became even a more paradigmatic trend (Kersting & Meyer, 2018).

Clearly, all these changes have had to influence the Digital Humanities, from where many questions can be formulated: How the academic studies on Digital Humanities have assimilated the Big Data and Artificial Intelligence revolutions? Are the waves detected by Berry still valid or there are needed new ones? What are, more specifically, the trends and approaches that are dominating the most recent studies on Digital Humanities? Even more, what texts and authors were the most influential ones to carry on these transformations?

Interactive Exploratory Analysis

To answer these questions, I propose a Digital Humanities Interactive Exploratory Analysis, reviewing historic academic production . The analysis was performed over the academic database Scopus, from where there were downloaded a total of 3237 documents replying to the query “digital humanities”. With this intention, the collected database was analyzed with R programming tools, mainly with packages such as bibliometrix (Aria & Cucurullo, 2021), widyr (Robinson, 2020) and tidytext (Robinson & Silge, 2020). Some of the applied statistics were: keyword frequencies and its clusterization, co-occurrence and co-citation network analysis, word correlations and their associations within the documents.

For the purpose of socialize the study, I deployed the findings in a public site that will also be the product presented during the meeting. The site will contain the most significant visualizations in an interactive mode, using plotly (Sievert et al., 2021) and shiny (Chang et al., 2021) packages. Furthermore, the network visualizations will be performed by gephi (Bastian & Ramos Ibañez, 2017) and its interactive plugin Sigma JS (Jacomy, 2017).

References

Aria, M., & Cucurullo, C. (2021). bibliometrix: Comprehensive Science Mapping Analysis (3.1.4) [Computer software]. https://cran.r-project.org/package=bibliometrix

Bastian, M., & Ramos Ibañez, E. (2017). Gephi. Makes graphs handy (0.9.2) [Computer software]. Gephi Consortium. https://gephi.org/

Berry, D. M. (2011). The computational turn: Thinking about the digital humanities. The Computational Turn: Thinking about the Digital Humanities, 12. https://sro.sussex.ac.uk/id/eprint/49813/1/BERRY_2011-THE_COMPUTATIONAL_TURN_THINKING_ABOUT_THE_DIGITAL_HUMANITIES.pdf

Chang, W., Cheng, J., Allaire, J., Sievert, C., Barret, S., Yihui, X., Allen, J., McPherson, J., Dipert, A., & Borges, B. (2021). shiny: Web Application Framework for R (1.6.0) [Computer software]. https://cran.r-project.org/package=shiny

Jacomy, A. (2017). Sigma.js (1.2.1) [Computer software]. http://sigmajs.org/

Kersting, K., & Meyer, U. (2018). From Big Data to Big Artificial Intelligence?: Algorithmic Challenges and Opportunities of Big Data. KI – Künstliche Intelligenz, 32(1), 3–8. https://doi.org/10.1007/s13218-017-0523-7

Robinson, D. (2020). widyr: Widen, Process, then Re-Tidy Data (0.1.3) [Computer software]. https://cran.r-project.org/package=widyr

Robinson, D., & Silge, J. (2020). tidytext: Text Mining using “dplyr”, “ggplot2”, and Other Tidy Tools (0.2.4) [Computer software]. https://cran.r-project.org/package=tidytext

Sievert, C., Parmer, C., Hocking, T., Chamberlain, S., Ram, K., Corvellec, M., & Despouy, P. (2021). plotly: Create Interactive Web Graphics via “plotly.js” (4.9.4.1) [Computer software]. https://cran.r-project.org/package=plotly

Wickham, H. (2021). tidyverse: Easily Install and Load the “Tidyverse” (1.3.1) [Computer software]. https://cran.r-project.org/package=tidyverse