Word clouds provide a quick and visually appealing way to showcase textual content and they have been in use since the 90s. However, they lack precision, interactivity, and context. We developed a methodology and a word visualization tool that can take word clouds to the next level, making them much more useful not only for visualization, but also for research and educational purposes.
How to use speech-to-text network visualization as a direct feedback tool for teachers and students.
Text network visualizations are most often used to study and analyze data. However, how can an analytical tool become a musical instrument and what are the implications of that, both for the research process and for the creative work?
In this tutorial we present a method for topic modeling using text network analysis (TNA) and visualization. The approach we propose is based on identifying topical clusters in text based on co-occurrence of words. We will demonstrate how this approach can be used for topic modeling, how it compares to Latent Dirichlet Allocation (LDA), and how they can be used together to provide more relevant results.
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.
