Pith. sign in

REVIEW 1 cited by

Popularity and Performance: A Large-Scale Study

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1406.7729 v1 pith:FYLCINPM submitted 2014-06-30 cs.SI physics.soc-ph

classification cs.SIphysics.soc-ph
keywords popularityqualitypopulareffectlarge-scaleoptionsbecausebecome
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Social scientists have long sought to understand why certain people, items, or options become more popular than others. One seemingly intuitive theory is that inherent value drives popularity. An alternative theory claims that popularity is driven by the rich-get-richer effect of cumulative advantage---certain options become more popular, not because they are higher quality, but because they are already relatively popular. Realistically, it seems likely that popularity is driven by neither one of these forces alone but rather both together. Recently, researchers have begun using large-scale online experiments to study the effect of cumulative advantage in realistic scenarios, but there have been no large-scale studies of the combination of these two effects. We are interested in studying a case where decision-makers observe explicit signals of both the popularity and the quality of various options. We derive a model for change in popularity as a function of past popularity and past perceived quality. Our model implies that we should expect an interaction between these two forces---popularity should amplify the effect of quality, so that the more popular an option is, the faster we expect it to increase in popularity with better perceived quality. We use a data set from eToro.com, an online social investment platform, to support this hypothesis.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. When Influence Misleads: Informational and Strategic Limits of Social Learning in Trading Networks

    physics.soc-ph 2025-07 reject novelty 5.0 of 10

    On eToro, traders mirror popular investors rather than profitable ones, and the simulation used to argue for performance-based signals depends on an autocorrelation in returns that the data do not show.

Pith tools