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Text Visualization and Visual Text Analytics

Nowadays, the availability of texts and documents is overwhelming, and people want to actively deal with them to solve specific problems. Besides traditional sources of textual data such as books, written communication (e.g., letters), and linguistic corpora, massive amounts of texts are created online as part of digital communication, websites, forums, and social media. It is difficult and, in many cases, impossible to investigate such data sets by the means of close reading; relying exclusively on computational text mining approaches can also be problematic, for instance, if the output of such computational models is difficult to interpret.

We are developing text analytics tools that combine interactive visualization with natural language processing approaches. This combination will make it possible for human beings to make sense of large and dynamic text data and allows for exploration, control, and final evaluation of the analysis processes and results. Such methods are crucial for many application fields, including intelligence and security analytics, crisis management systems, business intelligence, or social media monitoring.

Contact Persons:

  • Prof. Dr. Andreas Kerren
  • Dr. Kostiantyn Kucher

Relevant Publications:

  • Publications in DiVA

Relevant Projects:

  • AI4ClimateAdaptation
  • Multiscale Visual Analytics of Dynamic Multivariate Networks Derived from Text Streams

Relevant Tools:

  • Text Visualization Browser
  • SentimentVis Browser
  • VA+Embeddings Browser
  • Word Rain

Interesting URLs:

  • Sparklines Literature (Word-Sized Graphics for Scientific Texts)
  • Search User Interfaces

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