Network Visualization for Digital Humanities: Two Case Studies of Visual Analyses for Text Analytics
2016 (English)In: International Symposium on Digital Humanities, Växjö 7-8 November 2016: Book of Abstracts, Linnaeus University , 2016, 39-43 p.Conference paper, Abstract (Refereed)
Much of the data created nowadays in fields such as Digital Humanities (DH) is of relational nature, such as social or semantic networks. Researchers often decide to depict networks as node-link diagrams to make a better sense of the complex nature of data. Understanding the topology of such a network can be very important. For instance, if we show our friends as network nodes and their friendship as edges between the nodes, it becomes easy to identify groups of friends from different social settings (work friends, high school friends, etc.).
Networks usually have additional attributes attached to their elements. For instance, we can model a number of documents in a repository as nodes and use edges to describe co-authorship. Additionally, we might want to explore other aspects of such a corpus, like the keywords for each document, its genre, and various other data associated. Here, it is often desirable to get an overview about the network structure and how different data values relate to this structure. In this paper, we present two case studies for visualizations in DH with a focus on publication networks. But first, we will introduce our data sets used in these studies.
Place, publisher, year, edition, pages
Linnaeus University , 2016. 39-43 p.
digital humanities, networks, visualization, social networks, interaction
Computer Science Human Computer Interaction
Research subject Computer Science, Information and software visualization; Computer and Information Sciences Computer Science, Media Technology
IdentifiersURN: urn:nbn:se:lnu:diva-57762OAI: oai:DiVA.org:lnu-57762DiVA: diva2:1044053
International Symposium on Digital Humanities, Växjö, Sweden, November 7-8, 2016.