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Abstract

The Internet Movie Database (IMDb) is one of the most-visited websites in the world and the premier source for information on films. Similar to Wikipedia, much of IMDb's information is user contributed. IMDb also allows users to voice their opinion on the quality of films through voting. We investigate whether there is a connection between user voting data and economic film characteristics. We perform distribution and correlation analysis on a set of films chosen to mitigate effects of bias due to the language and country of origin of films. Production budget, box office gross, and total number of user votes for films are consistent with double-log normal distributions for certain time periods. Both total gross and user votes are consistent with a double-log normal distribution from the late 1980s onward while for budget it extends from 1935 to 1979. In addition, we find a strong correlation between number of user votes and the economic statistics, particularly budget. Remarkably, we find no evidence for a correlation between number of votes and average user rating. Our results suggest that total user votes is an indicator of a film's prominence or notability, which can be quantified by its promotional costs.

Type

a

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Abstract

Two methods for comparing impact factors and citation rates across fields of science are tested against each other using citations to the 3,705 journals in the Science Citation Index 2010 (CD-Rom version of SCI) and the 13 field categories used for the Science and Engineering Indicators of the U.S. National Science Board. We compare (a) normalization by counting citations in proportion to the length of the reference list (1/N of references) with (b) rescaling by dividing citation scores by the arithmetic mean of the citation rate of the cluster. Rescaling is analytical and therefore independent of the quality of the attribution to the sets, whereas fractional counting provides an empirical strategy for normalization among sets (by evaluating the between-group variance). By the fairness test of Radicchi and Castellano (), rescaling outperforms fractional counting of citations for reasons that we consider.

Type

a