Machines that learn how to code open-ended survey data

作     者：Esuli, Andrea Sebastiani, Fabrizio 

作者机构：CNR Ist Sci & Tecnol Informaz I-56124 Pisa Italy 

出 版 物：《INTERNATIONAL JOURNAL OF MARKET RESEARCH》 (国际市场研究杂志)

年 卷 期：2010年第52卷第6期

页      面：775-800页

核心收录：

学科分类：12[管理学] 120202[管理学-企业管理（含：财务管理、市场营销、人力资源管理）] 0202[经济学-应用经济学] 02[经济学] 1202[管理学-工商管理] 020205[经济学-产业经济学] 

主　　题：CONSUMERS -- Attitudes COMPUTER software development MARKETING research SENTIMENT analysis CONSUMERS' preferences CONSUMER research CONSUMER science COMPUTATIONAL linguistics SURVEYS CODING theory TEXT mining (Information retrieval) CONTENT analysis (Communication) 

摘      要：We describe an industrial-strength software system for automatically coding open-ended survey responses. The system is based on a learning metaphor, whereby automated verbatim coders are automatically generated by a general-purpose process that learns, from a user-provided sample of manually coded verbatims, the characteristics that new, uncoded verbatims should have in order to be attributed the codes in the codeframe. In this paper we discuss the basic workings of this software and present the results of experiments we have run on several datasets of real respondent data, in which we have compared the accuracy of the software against the accuracy of human coders.