The paper Revealing Relations between Open and Closed Answers in Questionnaires through Text Clustering Evaluation which I’ve written together with Magnus Rosell (PhD student at CSC, KTH) has been accepted to the 6th edition of the Language Resources and Evaluation Conference (LREC) which will be held in Marrakech, Morocco 26th May – 1st June 2008. The conference is one of the major events on Language Resources (LRs) and Evaluation for Human Language Technologies (HLT). The experiments described in the paper will be developed further and applied on other data sets as part of my PhD studies.
Open answers in questionnaires contain valuable information that is very time-consuming to analyze manually. We present a method for hypothesis generation from questionnaires based on text clustering. Text clustering is used interactively on the open answers, and the user can explore the cluster contents. The exploration is guided by automatic evaluation of the clusters against a closed answer regarded as a categorization. This simplifies the process of selecting interesting clusters. The user formulates a hypothesis from the relation between the cluster content and the closed answer categorization. We have applied our method on an open answer regarding occupation compared to a closed answer on smoking habits. With no prior knowledge of smoking habits in different occupation groups we have generated the hypothesis that farmers smoke less than the average. The hypothesis is supported by several separate surveys. Closed answers are easy to analyze automatically but are restricted and may miss valuable aspects. Open answers, on the other hand, fully capture the dynamics and diversity of possible outcomes. With our method the process of analyzing open answers becomes feasible.
The full paper can be found here: