Prostate cancer is a complex topic. Large number of scientific papers have been written as the research continues towards identifying a cure. A key part of the search strategy is to explore the relationship between prostate cancer and other potential influencers– such as forms of treatment or risk factors. For example, is there any evidence to suggest a link between coffee consumption and prostate cancer? Many of these linkages maybe obvious, with large bodies of evidence to support or refute the connection. But what about those curious, unexpected relationships that may lie buried deep within the body of literature, rendered virtually invisible by their rarity or counter-intuitive nature?
Sophisticated analysis of documents by text mining techniques, followed by visualisation of results by ‘knot analysis’ can reveal surprising insights into any topic. ‘Knot analysis’ is one way to illustrate the connections between topics in large, complex document sets. Coloured traces on the diagram relate to specific words or phrases in the texts. All traces start at the same point, and at each instance of the specified word (i.e. ‘prostate’ or ‘men’ in this example), the trace makes a turn. Tightly knotted traces indicate many occurrences of the word in the texts, traces with long straight lines are indicative of lower incidences of the selected word. Traces which lie over each other suggest linkages between topics in the texts, while traces which are separate indicate no linkage between topics (e.g. ‘women’ and ‘prostate’ in the diagram below).