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Mass Collaboration on the Web: Textual Content Analysis by Means of Natural Language Processing

Habernal, Ivan and Daxenberger, Johannes and Gurevych, Iryna
Cress, Ulrike and Moskaliuk, Johannes and Jeong, Heisawn (eds.) (2016):
Mass Collaboration on the Web: Textual Content Analysis by Means of Natural Language Processing.
In: Mass Collaboration and Education, Springer International Publishing, pp. 367-390, DOI: 10.1007/978-3-319-13536-6_18,
[Online-Edition: http://doi.org/10.1007/978-3-319-13536-6_18],
[Book Section]

Abstract

This chapter describes perspectives for utilizing natural language processing (NLP) to analyze artifacts arising from mass collaboration on the web. In recent years, the amount of user-generated content on the web has grown drastically. This content is typically noisy and un- or at best semi-structured, so that traditional analysis tools cannot properly handle it. To discover linguistic structures in this data, manual analysis is not feasible due to the large quantities of data. In this chapter, we explain and analyze web-based resources of mass collaboration, namely, wikis, web forums, debate platforms, and blog comments. We introduce recent advances and ongoing efforts to analyze textual content in two of these resources with the help of NLP. This includes an approach to discover flows of knowledge in online mass collaboration as well as methods to mine argumentative structures in natural language text. Finally, we outline application scenarios of the previously discussed techniques and resources within the domain of education.

Item Type: Book Section
Erschienen: 2016
Editors: Cress, Ulrike and Moskaliuk, Johannes and Jeong, Heisawn
Creators: Habernal, Ivan and Daxenberger, Johannes and Gurevych, Iryna
Title: Mass Collaboration on the Web: Textual Content Analysis by Means of Natural Language Processing
Language: English
Abstract:

This chapter describes perspectives for utilizing natural language processing (NLP) to analyze artifacts arising from mass collaboration on the web. In recent years, the amount of user-generated content on the web has grown drastically. This content is typically noisy and un- or at best semi-structured, so that traditional analysis tools cannot properly handle it. To discover linguistic structures in this data, manual analysis is not feasible due to the large quantities of data. In this chapter, we explain and analyze web-based resources of mass collaboration, namely, wikis, web forums, debate platforms, and blog comments. We introduce recent advances and ongoing efforts to analyze textual content in two of these resources with the help of NLP. This includes an approach to discover flows of knowledge in online mass collaboration as well as methods to mine argumentative structures in natural language text. Finally, we outline application scenarios of the previously discussed techniques and resources within the domain of education.

Title of Book: Mass Collaboration and Education
Series Name: Computer-Supported Collaborative Learning Series
Volume: 16
Publisher: Springer International Publishing
ISBN: 978-3-319-13535-9
Uncontrolled Keywords: UKP_a_LangTech4eHum;UKP_p_TextAsProcess;UKP_invited;UKP_reviewed;UKP_a_ArMin;UKP_a_TexMinAn
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 1994 Adaptive Preparation of Information from Heterogeneous Sources
Date Deposited: 31 Dec 2016 14:29
DOI: 10.1007/978-3-319-13536-6_18
Official URL: http://doi.org/10.1007/978-3-319-13536-6_18
Identification Number: TUD-CS-2015-0083
Related URLs:
Projects: CEDIFOR
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