Fisheye Word Cloud for temporal sentiment exploration

This poster abstract presents a new word cloud technique, the Fisheye Word Cloud, for exploring time-series data in a focused+context approach to analyzing word data. Our design has two features: cursor-centric layout and word cloud generation on demand. We conducted a validation study to evaluate how our Fisheye Word Cloud influences user performance in comparison tasks of time-series data. Based on task completion time and a TLX-based Likert-style questionnaire, we found the Fisheye Word Cloud has faster task completion time and a better user satisfaction level than the alternative we reviewed.

Citation

Wang, J.; Dent, K.; North, C. Fisheye Word Cloud for temporal sentiment exploration. ACM CHI 2013 Extended Abstracts on Human Factors in Computing Systems; 2013 April 27 - May 2; Paris, France. NY: ACM; 2013; 1767-1772.