Nice grey life

Humanities and big data in Ibero-America • Theory, methodology and practical applications

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Digital humanities is a young–though established–field. It deals with different expressions in which digital data manipulation techniques can be applied and used to analyze subjects that are identified as belonging to the humanities. Although most often used to analyze different aspects of literature or social network analysis, it can also be applied to other humanistic disciplines or artistic expressions. Digital humanities employs many tools, but those categorized as big data are among the most frequently employed. This book samples different takes on digital humanities, with the particularity that it focuses on Ibero-American uses. It is worth noting that this book is the second in a series of four volumes, published or set to be published between 2022 and 2026. Being the output of a field survey, I perceive this book to be targeted towards fellow Digital Humanists – people interested in applying computational methods to further understand and research topics in the humanities. It is not a technical book in the sense Computer Science people would recognize as such, but several of the presented works do benefit from understanding some technical concepts.

The 12 articles (plus an introduction) that make up this book are organized in three parts:

(1) “Theoretical Framework” presents the ideas and techniques of data science (that make up the tools for handling big data), and explores how data science can contribute to literary analysis, all while noting that many such techniques are usually frowned upon in Latin America as data science “smells neoliberal”;

(2) “Methodological Issues” looks at specific issues through the lens of how they can be applied to big data, with specific attention given to works in Spanish; and

(3) “Practical Applications” analyzes specific Spanish works and communities based on big data techniques.

Several chapters treat a recurring theme: the simultaneous resistance and appropriation of big data by humanists. For example, at least three of the chapters describe the tensions between humanism (“aesthesis”) and cold, number-oriented data analysis (“mathesis”).

The analyzed works of Parts 2 and 3 are interesting and relatively easy to follow.

Some inescapable ideological gleans from several word uses – from the book’s and series’ name, which refers to the Spanish-speaking regions as “Ibero-America”, often seen as Eurocentric, in contrast with the “Latin America” term much more widely used throughout the region.

I will end with some notes about the specific versions of the book I reviewed. I read both an EPUB version and a print copy. The EPUB did not include links for easy navigation to footnotes, that is, the typographical superindexes are not hyperlinked to the location of the notes, so it is very impractical to try to follow them. The print version (unlike the EPUB) did not have an index, that is, the six pages before the introduction are missing from the print copy I received. For a book such as this one, not having an index hampers the ease of reading and referencing.

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