4. CONCLUSION
In this study we analyzed time series data on the edit processes of FAs and FFAs. Although the time
series data exhibited different trajectories for different articles, we observed a number of stable patterns in
the trajectories. The patterns appeared to follow the life cycles of the underlying entities.
An analysis of FAR and FARC discussions on FFAs showed that IQ could be changed not only actively
by editors, malicious agents, or IQAs editing the article, but also passively by changes in the article’s
underlying entity or the context of its evaluation and use. The IQ of the majority of FFAs had been
reevaluated as lower, and these FFAs lost their high-quality status after the community decided to
increase IQ requirements.
We believe that this study of the patterns and sources of IQ variance in Wikipedia can contribute to a
better understanding of IQ dynamics, and that it has useful implications for optimizing IQ assurance in
traditional databases. In particular, the activity theoretic model of IQ change and information type specific
edit process patterns identified in this study can serve as a reusable knowledge resource for predicting IQ
changes and guiding IQ maintenance actions and resource allocation. The model can also inform the
design of software architecture and tools for automatic IQ assurance. Future work will include
investigating the cost structure of IQ and linking it to IQ decision making.