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In this article, we present a focus + context display technique to support multifaceted viewing of word clouds. In our algorithm, the sizes of words in a word cloud are first changed to reflect the current importance metric selected by the user and then scaled to balance space utilization and word readability. To remove word overlaps caused by changes of sizes while maintaining the positional dependency modeled by a directed acyclic graph, we propose a force-directed model that also maximizes the utilization of display space. We demonstrate the effectiveness and usefulness of our techniques through case studies using a real-world dataset and evaluate the performance of the constraint-based overlap removal method in achieving stable layouts during importance transformation.<\/jats:p>","DOI":"10.1177\/1473871614534095","type":"journal-article","created":{"date-parts":[[2014,5,12]],"date-time":"2014-05-12T21:32:01Z","timestamp":1399930321000},"page":"168-180","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["Supporting multifaceted viewing of word clouds with focus+context display"],"prefix":"10.1177","volume":"14","author":[{"given":"Xiaotong","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, 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