Dynamics of Content Quality in Collaborative Knowledge Production
By Emilio Ferrara, Nazanin Alipourfard, Keith A. Burghardt, Chiranth Gopal, Kristina Lerman. 2017
15 citations recorded by the source corpus.
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.
Subfields: Communication, Information Systems, Social Sciences & Humanities
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Citations in the corpus
- Using Simpson's Paradox to Discover Interesting Patterns in Behavioral Data (2018, background): “Indeed, a study of Stack Exchange observed short term deterioration in performance (Ferrara et al. 2017).”
- Can you Trust the Trend?: Discovering Simpson's Paradoxes in Social Data (2018, methodology): “This deterioration was observed for the quality of answers written on Stack Exchange [9], comments posted on Reddit [19], and the time spent reading posts on Facebook [15].”
- Computational social scientist beware: Simpson’s paradox in behavioral data (2017, background): “…of dynamics of user performance on Stack Exchange found that answer quality, as measured by the probability that it will be accepted by the asker as the best answer, declines steadily over the course of a session, with each successive answer written by a user ever less likely to get accepted [7].”