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

  • Ivan HabernalEmail author
  • Johannes Daxenberger
  • Iryna Gurevych
Chapter
Part of the Computer-Supported Collaborative Learning Series book series (CULS, volume 16)

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.

Keywords

Collaboration Mass collaboration Natural language processing Wikis Discussion forums 

Notes

Acknowledgments

This work has been supported by the Volkswagen Foundation as part of the Lichtenberg-Professorship Program under grant No. I/82806 and by the German Institute for Educational Research (DIPF).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Ivan Habernal
    • 1
    • 2
    Email author
  • Johannes Daxenberger
    • 1
  • Iryna Gurevych
    • 1
    • 2
  1. 1.Ubiquitous Knowledge Processing Lab, Department of Computer ScienceTU DarmstadtDarmstadtGermany
  2. 2.German Institute for Educational ResearchFrankfurt am MainGermany

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