NDLI: The ACODEA framework: Developing segmentation and classification schemes for fully automatic analysis of online discussions

Content Provider	Springer Nature Link
Author	Mu, Jin Stegmann, Karsten Mayfield, Elijah Rosé, Carolyn Fischer, Frank
Copyright Year	2012
Abstract	Research related to online discussions frequently faces the problem of analyzing huge corpora. Natural Language Processing (NLP) technologies may allow automating this analysis. However, the state-of-the-art in machine learning and text mining approaches yields models that do not transfer well between corpora related to different topics. Also, segmenting is a necessary step, but frequently, trained models are very sensitive to the particulars of the segmentation that was used when the model was trained. Therefore, in prior published research on text classification in a CSCL context, the data was segmented by hand. We discuss work towards overcoming these challenges. We present a framework for developing coding schemes optimized for automatic segmentation and context-independent coding that builds on this segmentation. The key idea is to extract the semantic and syntactic features of each single word by using the techniques of part-of-speech tagging and named-entity recognition before the raw data can be segmented and classified. Our results show that the coding on the micro-argumentation dimension can be fully automated. Finally, we discuss how fully automated analysis can enable context-sensitive support for collaborative learning.
Starting Page	285
Ending Page	305
Page Count	21
File Format	PDF
ISSN	15561607
Journal	International Journal of Computer-Supported Collaborative Learning
Volume Number	7
Issue Number	2
e-ISSN	15561615
Language	English
Publisher	Springer US
Publisher Date	2012-05-16
Publisher Institution	International Society of the Learning Sciences
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Online discussion Automatic content analysis Text classification Educational Technology Cognitive Psychology Computers and Education User Interfaces and Human Computer Interaction Learning & Instruction
Content Type	Text
Resource Type	Article
Subject	Education Human-Computer Interaction

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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