Visual Computing

University of Konstanz
IEEE Transactions on Visualization and Computer Graphics

EdWordle: Consistency-Preserving Word Cloud Editing

Y. Wang, X. Chu, C. Bao, L. Zhu, O. Deussen, B. Chen, M. Sedlmair
Teaser of EdWordle: Consistency-Preserving Word Cloud Editing


Paper (.pdf, 4.3 MB)


We present EdWordle, a method for consistently editing word clouds. At its heart, EdWordle allows users to move and edit words while preserving the neighborhoods of other words. To do so, we combine a constrained rigid body simulation with a neighborhood-aware local Wordle algorithm to update the cloud and to create very compact layouts. The consistent and stable behavior of EdWordle enables users to create new forms of word clouds such as storytelling clouds in which the position of words is carefully edited. We compare our approach with state-of-the-art methods and show that we can improve user performance, user satisfaction, as well as the layout itself.


  author     = {Y. Wang and X. Chu and C. Bao and L. Zhu and O. Deussen and B. Chen and M. Sedlmair},
  doi        = {10.1109/TVCG.2017.2745859},
  issn       = {1077-2626},
  journal    = {IEEE Transactions on Visualization and Computer Graphics},
  keywords   = {data visualisation;solid modelling;text editing;EdWordle;user performance;user satisfaction;consistency-preserving word cloud editing;constrained rigid body simulation;neighborhood-aware local Wordle algorithm;Tag clouds;Layout;Tools;Visualization;Semantics;Heuristic algorithms;Data visualization;Wordle;consistency;text visualization},
  month      = {jan},
  number     = {1},
  pages      = {647--656},
  title      = {EdWordle: Consistency-Preserving Word Cloud Editing},
  volume     = {24},
  year       = {2018},
  url        = {},