Analysis of Open Answers to Survey Questions through Interactive Clustering and Theme Extraction

Espinoza, Fredrik
Hamfors, Ola
Karlgren, Jussi
Olsson, Fredrik
Persson, Per
Hamberg, Lars
Sahlgren, Magnus

This paper describes design principles for and the implementation of Gavagai Explorer—a new application which builds on interactive text clustering to extract themes from topically coherent text sets such as open text answers to surveys or questionnaires.An automated system is quick, consistent, and has full coverage over the study material. A system allows an analyst to analyze more answers in a given time period; provides the same initial results regardless of who does the analysis, reducing the risks of inter-rater discrepancy; and does not risk miss responses due to fatigue or boredom. These factors reduce the cost and increase the reliability of the service. The most important feature, however, is relieving the human analyst from the frustrating aspects of the coding task, freeing the effort to the central challenge of understanding themes.

Presented as a Demo at the 2nd CHIIR Conference, 2018

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