1,785 research outputs found
Can Real Social Epistemic Networks Deliver the Wisdom of Crowds?
In this paper, we explain and showcase the promising methodology of testimonial network analysis and visualization for experimental epistemology, arguing that it can be used to gain insights and answer philosophical questions in social epistemology. Our use case is the epistemic community that discusses vaccine safety primarily in English on Twitter. In two studies, we show, using both statistical analysis and exploratory data visualization, that there is almost no neutral or ambivalent discussion of vaccine safety on Twitter. Roughly half the accounts engaging with this topic are pro-vaccine, while the other half are con-vaccine. We also show that these two camps rarely engage with one another, and that the con-vaccine camp has greater epistemic reach and receptivity than the pro-vaccine camp. In light of these findings, we question whether testimonial networks as they are currently constituted on popular fora such as Twitter are living up to their promise of delivering the wisdom of crowds. We conclude by pointing to directions for further research in digital social epistemology
Weighted citation: An indicator of an article's prestige
We propose using the technique of weighted citation to measure an article's
prestige. The technique allocates a different weight to each reference by
taking into account the impact of citing journals and citation time intervals.
Weighted citation captures prestige, whereas citation counts capture
popularity. We compare the value variances for popularity and prestige for
articles published in the Journal of the American Society for Information
Science and Technology from 1998 to 2007, and find that the majority have
comparable status.Comment: 17 pages, 6 figure
- …