Computer Graphics and Visual Computing (CGVC) 2018

Text visualization is a rapidly growing sub-field of information visualization and visual analytics. There are many approaches and techniques introduced every year to address a wide range of tasks and enable researchers from different disciplines to obtain leading-edge knowledge from digitized collections. This can be challenging particularly when the data is massive. Additionally, the sources of digital text have spread substantially in the last decades in various forms, such as web pages, blogs, twitter, email, electronic publications, and books. In response to the explosion of text visualization research literature, the first survey article was published in 2010. Furthermore, there are a growing number of surveys that review existing techniques and classify them based on text research methodology. In this work, we aim to present the first Survey of Surveys (SoS) that review all of the survey and state-of-the-art papers on text visualization techniques and provide an SoS classification. We study and compare the surveys, and categorize them into 5 groups: (1) document-centered, (2) user task analysis, (3) cross-disciplinary, (4) multifaceted, and (5) satellite-themed. We provide survey recommendations for researchers in the field of text visualization. The result is a very unique, valuable starting point and overview of the current state-of-the-art in text visualization research literature.

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