Interactive Exploratory Analysis for Digital Humanities Trends

The authors address for first time a large scale bibliometric approach -3,068 journal articles- to digital humanities, by performing a all-author co-citation analysis (ACA method) over 3 core journals on DH: Computers and the Humanities, Digital Humanities Quarterly, and Literacy and Linguistic Computing (now called Digital Scholarhip in the Humanities). They find five DH scholar clusters: (1) focused on “Leech, G”, (2) focused on “Miller, G”, (3) focused on “Nerbonne, J”, (4) focused on “Holmes, D.I”, and (5) focused on “McCarty, W”. The clusters distribution on the density map reveals that there is a clear separation between (4) and (5), which turn out to be denser than other clusters. This shows that these two clusters are more significant and have more citation influence.

The paper is an extension of the previous one, by adding to the ACA methodology, the informal space of social media data. The social network Twitter is incorporated, by analyzing 3,160 Twitter users and 5,929,609 tweets, creating a network of co-retweet analysis which is comparable to the co-citation network, but in an informal way. In the academic network, they identified distinct topic-based clusters of researchers with backgrounds in information studies and historical literature; in linguistics; in statistical text analysis; in early concordance projects; and biotech influenced text analysis. In contrast, the co-retweet network exhibits grouping based on language and region, with clusters related to scholars in North America; in Australia; in the UK; and clusters with Francophonic, Germanophonic and Hispanophonic backgrounds. They also noted that topics of academic study are less likely to change, meanwhile social media interconnections are more common.

The authors perform a bibliometric analysis covering the period 1989-2014. They applied co-authorship, article co-citation, and bibliographic coupling networks methods, as well as madularity maximization paritition. They use several network topology measures to identify the degree of topical diversity and intellectual cohesion of author collaboration in DH. The database was created by searching in Scopus the query (“digital humanities” OR “digital humanity” OR “humanities computing” OR “humanity computing”) and combined with a set of articles belonging to DH journals, generating a final set of 2115 articles, 2787 authors and 3469 keywords; slightly less than the current study. The conclusions emphasizes the great variety of subjects and keywords that converge in DH, which leads to an integration trend in the early 2000, when largest nodes of co-citation appear. However, they also found network fractures along geographic and language boundaries, with very few international collaborations. They propose that it can be caused because of the national or regional character of the humanities, but also due to the different acceptions that humanities may have in different countries. Finally, they found a lack of densely interconnected core of authors playing a role of network cohesion, resulting a very sparse case when it is compared with other domains.