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Author(s): Habernal, Ivan; Daxenberger, Johannes; Gurevych, Iryna
Title: Mass collaboration on the web. Textual content analysis by means of natural language processing
In: Cress, Ulrike;Moskaliuk, Johannes;Jeong, Heisawn (Hrsg.): Mass collaboration and education, Cham: Springer, 2016 , S. 367-390
DOI: 10.1007/978-3-319-13536-6_18
Publication Type: 4. Beiträge in Sammelwerken; Sammelband (keine besondere Kategorie)
Language: Englisch
Keywords: Argumentation; Computerlinguistik; Data Mining; Daten; Inhaltsanalyse; Text; Web log; Wiki; Wissen
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. (DIPF/Orig.)
DIPF-Departments: Informationszentrum Bildung