Categorizing Open-Ended Survey Responses

An application of document clustering for Categorizing Open-ended Survey Responses
Nishantha Medagoda, Ruvan Weerasinghe University of Colombo School of Computing Sri Lanka [e-mail] [e-mail] ABSTRACT Open ended questions are an essential and important part of survey questionnaires. They provide an opportunity for researchers to discover unanticipated information regarding the domain of study. However, they are problematic for processing since they are unstructured questions to which possible answers are not suggested, and the respondent is free to answer in his or her own words. This paper presents a method of categorizing such open ended survey responses. A document clustering technique is employed in this study to categorize responses to open-ended survey questions. The algorithm employs several natural language processing techniques to extract a classification of responses automatically. Two experiments were carried out to determine the effectiveness of the proposed algorithm which proved to be promising. Keywords—Open-ended questions, Clustering

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INTRODUCTION

Open ended questions in survey questionnaires are unstructured questions in which possible answers are not suggested, and which the respondent is expected to answer in his or her own words. When building a questionnaire for a statistical survey, it is essential to include such open-ended questions to gather unanticipated information. Open-ended questions are those questions that will elicit such additional information from the respondents. Since the freedom of answering these types of questions is given to the respondent, the respondent may write any answers which are related to the question. Such WH-questions usually begin with “how”, “what”, “when”, “where”, or “why”. Therefore there is no specific format for answers to these open-ended questions. In analyzing such responses we need to filter appropriate sentences, words from the responses. Often however, the responses to this type of

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