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2016
DOI: 10.1080/23311983.2016.1171458
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A social network analysis of Twitter: Mapping the digital humanities community

Abstract: International audienceDefining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic “discipline”. In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this “community of practice”. Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the “who’s following who?” graph allows us t… Show more

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Cited by 160 publications
(110 citation statements)
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“…Scholarly communities on Twitter have received significant attention in the literature over the last few years. Specific fields have included science (Weller & Puschmann, 2011), education (Veletsianos, 2012;Veletsianos & Kimmons, 2016), and the digital humanities (Quan-Haase, et al, 2015;Grandjean, 2016). At the end of their study of Twitter use by education scholars, Veletsianos and Kimmons (2016) noted areas for future research, including "the comparison of traditional scholarly output measures to Twitter impact metrics [and] the analysis of role, gender, race, and age differences regarding hashtag use" (p. 9).…”
Section: Social Media and Scholarly Communicationmentioning
confidence: 99%
See 1 more Smart Citation
“…Scholarly communities on Twitter have received significant attention in the literature over the last few years. Specific fields have included science (Weller & Puschmann, 2011), education (Veletsianos, 2012;Veletsianos & Kimmons, 2016), and the digital humanities (Quan-Haase, et al, 2015;Grandjean, 2016). At the end of their study of Twitter use by education scholars, Veletsianos and Kimmons (2016) noted areas for future research, including "the comparison of traditional scholarly output measures to Twitter impact metrics [and] the analysis of role, gender, race, and age differences regarding hashtag use" (p. 9).…”
Section: Social Media and Scholarly Communicationmentioning
confidence: 99%
“…Centrality is not one thing, but a family of concepts (Borgatti, 2013). We specifically utilized degree centrality in determining the most prominent members of #critlib, following established conventions in similar studies (Grandjean, 2016;Riddell, et al, 2017;Tremayne, 2014). Degree centrality is the sum of a node's ties.…”
Section: Social Network Analysismentioning
confidence: 99%
“…Complex systems often generate emergent properties 2 which are not contained in an obvious way in its parts. Examples of such networks range over all disciplines of science, including the study of social media networks 3 , scientific collaboration networks 4 and the human brain and its interconnected neurons as a particularly interesting one. The interactions between the components of a complex system define a network of connections consisting of nodes and edges.…”
Section: Introductionmentioning
confidence: 99%
“…It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks [18], message propagation in a social network service [19], friendship and acquaintance networks, collaboration graphs, kinship, disease transmission and sexual relationships [20,21]. These networks are often visualized through socio-grams, in which nodes are represented as points and ties are represented as lines.…”
Section: Network Analysis Indicatorsmentioning
confidence: 99%