A preliminary network visualisation of sentiments about machine vision as expressed in art, games and narratives.

Contexts in source publication

Context 1

... we had documented around 100 works, we began preliminary analysis of the coded data by exporting data into Gephi for network analysis, looking at different aspects of the data separately. Figure 2 shows a visualisation of the relationships between works and the sentiments we identified in each work. Clustering is done using the ForceAtlas2 algorithm in Gephi, which places nodes with shared connections closer to each other. ...

Context 2

... made the titles of works pale gray to emphasise the relationships between sentiments, and sized nodes by degree, so sentiment tags that have been applied to more works are larger than those that are rarely used. As Figure 2 shows, "helpful" is the most common sentiment. At this stage of research, we can't conclude that that means that machine vision is most often presented as helpful in art, games and narratives. ...

Context 3

... analysis is a useful and increasingly popular tool for exploring connections in a system. It is interesting to note the similarities between a network visualisation such as that shown in Figure 2, and hypertext, particularly spatial hypertext [16] and the map views commonly used for navigation in early hypertext systems like Hypercard and Storyspace [1]. Like hypertext, network analysis is a tool for thinking through connections. ...