Talks and Poster Presentations (with Proceedings-Entry):
D. Schall, F. Skopik:
"An Analysis of the Structure and Dynamics of Large-Scale Q/A Communities";
Talk: Advances in Databases and Information Systems 15th International Conference, ADBIS 2011,
- 2011-09-23; in: "Advances in Databases and Information Systems Proceedings of the 15th International Conference, ADBIS 2011",
J. Eder, M. Bielikova, A. Tjoa (ed.);
In recent years, the World Wide Web (WWW) has transformed
to a gigantic social network where people interact and collaborate
in diverse online communities. By using Web 2.0 tools, people
contribute content and knowledge at a rapid pace. Knowledge-intensive
social networks such as Q/A communities offer a great source of expertise for crowdsourcing applications. Companies desiring to outsource human tasks to the crowd, however, demand for certain guarantees such as quality that can be expected from returned tasks. We argue that the quality of crowd-sourced tasks greatly depends on incentives and the users' dynamically evolving expertise and interests. Here we propose expertise mining techniques that are applied in online social communities. Our approach recommends users by considering contextual properties of Q/A communities such as participation degree and topic-sensitive expertise.
Furthermore, we discuss prediction mechanisms to estimate answering
dynamics considering a personīs interest and social preferences.
Online communities, Expertise mining, Crowdsourcing
Project Head Schahram Dustdar:
Created from the Publication Database of the Vienna University of Technology.