Inverse Dynamical Inheritance in Stack Exchange Taxonomies

Authors

  • César Ojeda Fraunhofer Institute for Intelligent Analysis and Information Systems
  • Kostadin Cvejoski Fraunhofer Institute for Intelligent Analysis and Information Systems
  • Rafet Sifa Fraunhofer Institute for Intelligent Analysis and Information Systems
  • Christian Bauckhage Fraunhofer Institute for Intelligent Analysis and Information Systems

DOI:

https://doi.org/10.1609/icwsm.v11i1.14932

Abstract

Question Answering websites are popular repositories of expert knowledge and cover areas as diverse as linguistics, computer science, or mathematics. Knowledge is commonly organized via user defined tags which implicitly create population folksonomies. However, the interplay between latent knowledge structures and the answering behavior of users has not been fully explored yet. Here, we propose a model of a dynamical tagging process guided by taxonomies, devise a robust algorithm that allow us to uncover hidden topic hierarchies, apply our method to analyze several Stack Exchange websites. Our results show that the dynamics of the system strongly correlate with uncovered taxonomies.

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Published

2017-05-03

How to Cite

Ojeda, C., Cvejoski, K., Sifa, R., & Bauckhage, C. (2017). Inverse Dynamical Inheritance in Stack Exchange Taxonomies. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), 644-647. https://doi.org/10.1609/icwsm.v11i1.14932

Issue

Vol. 11 No. 1 (2017): Eleventh International AAAI Conference on Web and Social Media

Section

Poster Papers