Visualizing Human Factors and Ergonomics Publications

Abstract

Objective: This paper explores the strengths and limits of word clouds and word networks in visualizing the field of Human Factors and Ergonomics (HFE). Background: Large volumes of textual data present unique analysis and visualization challenges. Visualization techniques for these and other types of data must balance the need to make graphics engaging, accessible, and informative. Method: The analysis considers 11,911 abstracts from two decades of papers published in 11 HFE journals. A common graphical representation of text data—word clouds—is compared with word networks. Results: Word clouds and word networks both reveal key terms of HFE, but word networks provide additional information regarding the sematic structure of the field. Restyling what has become known as the “mullet of the internet” could make a valuable contribution to analyzing textual data. Conclusion: Like other visualization techniques, word networks offer more insight, but with the cost of being less accessible than the simpler word clouds. Application: Word networks offer a promising alternative to word clouds in providing a more complete view of textual data than is possible with word clouds.