Dynamics of Content Quality in Collaborative Knowledge Production


  • Emilio Ferrara University of Southern California
  • Nazanin Alipoufard University of Southern California
  • Keith Burghardt University of California, Davis
  • Chiranth Gopal PES Institute of Technology
  • Kristina Lerman University of Southern California




We explore the dynamics of user performance in collaborative knowledge production by studying the quality of answers to questions posted on Stack Exchange. We propose four indicators of answer quality: answer length, the number of code lines and hyperlinks to external web content it contains, and whether it is accepted by the asker as the most helpful answer to the question. Analyzing millions of answers posted over the period from 2008 to 2014, we uncover regular short-term and long-term changes in quality. In the short-term, quality deteriorates over the course of a single session, with each successive answer becoming shorter, with fewer code lines and links, and less likely to be accepted. In contrast, performance improves over the long-term, with more experienced users producing higher quality answers. These trends are not a consequence of data heterogeneity, but rather have a behavioral origin. Our findings highlight the complex interplay between short-term deterioration in performance, potentially due to mental fatigue or attention depletion, and long-term performance improvement due to learning and skill acquisition, and its impact on the quality of user-generated content.




How to Cite

Ferrara, E., Alipoufard, N., Burghardt, K., Gopal, C., & Lerman, K. (2017). Dynamics of Content Quality in Collaborative Knowledge Production. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), 520-523. https://doi.org/10.1609/icwsm.v11i1.14907