
SUMMARYThis paper proposes chance index that estimates whether a node is chance in a co‐occurrence network. Recently, chance discovery researches are attractive for several domains. By using chance discovery, we can develop new business or predict earthquake. However, there is a problem that chance discovery requires analysts’ inference from visualized network so that success and failure of chance discovery depend on analysists. In order to solve this problem, we analyzed the features from previous chance discovery researches and build the two hypotheses: (1) chance nodes have high betweenness centrality and (2) chance nodes connect to others with weak links. Based on the hypotheses, chance index is formulated by two terms about betweenness centrality and the strength of links. We confirm the usability of chance index from verification experiments, using Bush network, questionnaire network, interview network, and editorial network.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
