基于交互式聚类和主题抽取的调查问题开放性答案分析

Fredrik Espinoza, Ola Hamfors, Jussi Karlgren, Fredrik Olsson, Per Persson, L. Hamberg, Magnus Sahlgren
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引用次数: 6

摘要

本文描述了Gavagai Explorer的设计原则和实现,这是一个新的应用程序,它建立在交互式文本聚类的基础上,从主题一致的文本集中提取主题,比如调查或问卷的开放文本答案。一个自动化的系统是快速的,一致的,并且对学习材料有全面的覆盖。系统允许分析人员在给定的时间段内分析更多的答案;无论谁进行分析,都能提供相同的初始结果,降低了评估者之间差异的风险;也不会因为疲劳或无聊而错过回应。这些因素降低了成本,提高了服务的可靠性。然而,最重要的特性是将人类分析师从编码任务中令人沮丧的方面解脱出来,将精力释放到理解主题的核心挑战上。Gavagai Explorer可以在线使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Open Answers to Survey Questions through Interactive Clustering and Theme Extraction
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 fatige 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. Gavagai Explorer is available on-line.
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