An Automatic Occupation and Industry Coding System in Sociology

• Takahashi Kazuko

  Keiai University

• Taki Hirofumi

  Hosei University

• Tanabe Shunsuke

  Waseda University

• Wei Li

  Tokyo Institute of Technology (Currently, CBA-Japan)

Bibliographic Information

Other Title

• 社会学における職業・産業コーディング自動化システムの活用
• シャカイガク ニ オケル ショクギョウ ・ サンギョウ コーディング ジドウカ システム ノ カツヨウ

Abstract

In sociology, occupation and industry variables are as important as sexual and age variables. For the purpose of statistical processing, answers collected from open-ended questions in social surveys need to be converted into code, which requires considerable time and effort and often results in inconsistencies in large scale surveys. This work deals with occupation and industry coding. In this work, we develop an automatic system using hand-crafted rules and Support Vector Machines. Our system can assign three candidate codes to an answer and estimates the confidence level of the primary predicted code for each national/international standard code sets. The system has now been released through the website of the Center for Social Research and Data Archives. The user can get the required coding result by uploading the data file in a specific format.

Journal

• Journal of Natural Language Processing

  Journal of Natural Language Processing 24 (1), 135-170, 2017

  The Association for Natural Language Processing

Keywords

• Social Surveys
• Occupation and Industry Coding
• Automaic Coding System
• Three Grade Confidence Level
• Open to the Public through the Website

Details

• CRID: 1390282679451197952
• NII Article ID: 130006832496
• NII Book ID: AN10472659
• DOI: 10.5715/jnlp.24.135
• ISSN: 21858314
• ISSN: 13407619
• NDL BIB ID: 027988252
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I027988252
• Web Site: https://www.jstage.jst.go.jp/article/jnlp/24/1/24_135/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed