<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Crowston, Kevin</style></author><author><style face="normal" font="default" size="100%">Xiaozhong Liu</style></author><author><style face="normal" font="default" size="100%">Allen, Eileen E.</style></author><author><style face="normal" font="default" size="100%">Heckman, Robert</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Machine Learning and Rule-Based Automated Coding of Qualitative Data</style></title><secondary-title><style face="normal" font="default" size="100%">American Society for Information Science and Technology (ASIST) Annual Conference</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">FLOSS</style></keyword><keyword><style  face="normal" font="default" size="100%">NLP</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2010</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">http://crowston.syr.edu/sites/crowston.syr.edu/files/ml_nlp.pdf</style></url><url><style face="normal" font="default" size="100%">http://crowston.syr.edu/sites/crowston.syr.edu/files/ASIST poster 2p final.pdf</style></url></related-urls></urls><pub-location><style face="normal" font="default" size="100%">Pittsburgh, PA</style></pub-location><abstract><style face="normal" font="default" size="100%">Researchers often employ qualitative research approaches but large volumes of textual data pose considerable challenges to manual coding. In this research, we explore how to implement fully or semi-automatic coding on textual data (specifically, electronic messages) by leveraging Natural Language Processing (NLP). In particular, we compare the performance of human-developed NLP rules to those inferred by machine learning algorithms. The experimental results suggest that NLP with machine learning can be an effective way to assist researchers in coding qualitative data.

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