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Mining Social Science Publications for Survey Variables
[conference paper]
Corporate Editor
Association for Computational Linguistics (ACL)
Abstract Research in Social Science is usually based on survey data where individual research questions relate to observable concepts (variables). However, due to a lack of standards for data citations a reliable identification of the variables used is often difficult. In this paper, we present a work-in-pro... view more
Research in Social Science is usually based on survey data where individual research questions relate to observable concepts (variables). However, due to a lack of standards for data citations a reliable identification of the variables used is often difficult. In this paper, we present a work-in-progress study that seeks to provide a solution to the variable detection task based on supervised machine learning algorithms, using a linguistic analysis pipeline to extract a rich feature set, including terminological concepts and similarity metric scores. Further, we present preliminary results on a small dataset that has been specifically designed for this task, yielding modest improvements over the baseline.... view less
Keywords
publication; technical literature; artificial intelligence; computational linguistics; survey; social science; concept; algorithm; periodical; construction of indicators; data capture
Classification
Science of Literature, Linguistics
Information Science
Free Keywords
OpenMinTed
Collection Title
Proceedings of the Second Workshop on NLP and Computational Social Science
Document language
English
Publication Year
2017
Page/Pages
p. 47-52
Status
Postprint; peer reviewed
Licence
Creative Commons - Attribution-NonCommercial-ShareAlike 4.0