Material
Abstract
We present an analysis and visualization method for computing what distinguishes a given document collection from others. We determine topics that discriminate a subset of collections from the remaining ones by applying probabilistic topic modeling and subsequently approximating the two relevant criteria distinctiveness and characteristicness algorithmically through a set of heuristics. Furthermore, we suggest a novel visualization method called DiTop-View, in which topics are represented by glyphs (topic coins) that are arranged on a 2D plane. Topic coins are designed to encode all information necessary for performing comparative analyses such as the class membership of a topic, its most probable terms and the discriminative relations. We evaluate our topic analysis using statistical measures and a small user experiment and present an expert case study with researchers from political sciences analyzing two real-world datasets.
BibTeX
@article{Oelke2014ComparativeExplorationDocument,
acmid = {2771516},
address = {Chichester, UK},
author = {D. Oelke and H. Strobelt and C. Rohrdantz and I. Gurevych and O. Deussen},
doi = {10.1111/cgf.12376},
issn = {0167-7055},
issue_date = {June 2014},
journal = {Computer Graphics Forum},
keywords = {Categories and Subject Descriptors according to ACM CCS:, H.5.m [Information Systems]: Information Interfaces and Presentation-Miscellaneous},
month = {jun},
number = {3},
numpages = {10},
pages = {201--210},
publisher = {The Eurographs Association \&\#38; John Wiley \&\#38; Sons, Ltd.},
title = {Comparative Exploration of Document Collections: A Visual Analytics Approach},
volume = {33},
year = {2014},
url = {http://graphics.uni-konstanz.de/publikationen/Oelke2014ComparativeExplorationDocument},
}