Word clouds are used to generate visual summaries of text, however, they have one major deficiency: they completely lose track of the context. As a result, there is a risk of getting false meaningless results and making the wrong assumptions about the underlying data. Text network analysis and visualization can solve this problem.
How to build brand association maps using customer feedback and visualize the main topics as well as the connections between them.
Search engine optimization is a set of strategies used to promote certain content in search results. Using a combination of text mining and network visualization techniques, you can identify discrepancies between what the users search for and what they actually find. You can then create the content that bridges that gap, so that it’s shown at the top of the relevant search results.
In this case study we demonstrate how text network analysis can be used to identify the main topical threads of a conference that consists of several talks. We also show how it can be used to identify how closely those talks are related as well as to suggest collaborations between the speakers or relevant thematic threads for the audience.
