How a "Hit" is Born: The Emergence of Popularity from the Dynamics of Collective Choice

In recent times there has been a surge of interest in seeking out patterns in the aggregate behavior of socio-economic systems. One such domain is the emergence of statistical regularities in the evolution of collective choice from individual behavior. This is manifested in the sudden emergence of popularity or "success" of certain ideas or products, compared to their numerous, often very similar, competitors. In this paper, we present an empirical study of a wide range of popularity distributions, spanning from scientific paper citations to movie gross income. Our results show that in the majority of cases, the distribution follows a log-normal form, suggesting that multiplicative stochastic processes are the basis for emergence of popular entities. This suggests the existence of some general principles of complex organization leading to the emergence of popularity. We discuss the theoretical principles needed to explain this socio-economic phenomenon, and present a model for collective behavior that exhibits bimodality, which has been observed in certain empirical popularity distributions.Comment: 17 pages, 14 figures, A version of the work is published in Econophysics and Sociophysics: Trends and Perspectives, (eds.) Bikas K. Chakrabarti, Anirban Chakraborti, Arnab Chatterjee; Wiley-VCH, Berlin (2006); Chapter-15, pages: 417-44

Religion-based Urbanization Process in Italy: Statistical Evidence from Demographic and Economic Data

This paper analyzes some economic and demographic features of Italians living in cities containing a Saint name in their appellation (hagiotoponyms). Demographic data come from the surveys done in the 15th (2011) Italian Census, while the economic wealth of such cities is explored through their recent [2007-2011] aggregated tax income (ATI). This cultural problem is treated from various points of view. First, the exact list of hagiotoponyms is obtained through linguistic and religiosity criteria. Next, it is examined how such cities are distributed in the Italian regions. Demographic and economic perspectives are also offered at the Saint level, i.e. calculating the cumulated values of the number of inhabitants and the ATI, "per Saint", as well as the corresponding relative values taking into account the Saint popularity. On one hand, frequency-size plots and cumulative distribution function plots, and on the other hand, scatter plots and rank-size plots between the various quantities are shown and discussed in order to find the importance of correlations between the variables. It is concluded that rank-rank correlations point to a strong Saint effect, which explains what actually Saint-based toponyms imply in terms of comparing economic and demographic data.Comment: 55 pages, 70 refs., 21 figures, 15 tables; prepared for and to be published in Quantity & Qualit

Analyses of Baby Name Popularity Distribution in U.S. for the Last 131 Years

We examine the complete dataset of baby name popularity collected by U.S. Social Security Administration for the last 131 years (1880-2010). The ranked baby name popularity can be fitted empirically by a piecewise function consisting of Beta function for the high-ranking names and power-law function for low-ranking names, but not power-law (Zipf's law) or Beta function by itself.Comment: 6 figure

User Behavior in Mass Media Websites

Mass media websites can be worthy to understand user trends in web services. RTVE, the National Broadcaster in Spain is a sample of such kind of service. Trend points to a shorter user interaction over the last three years, and a more straight access to content. Besides the number of pages consumed in a visit is becoming smaller as well. This article reviews these trends with data obtained from public sources, and analyze the distribution of web pages in the client layer and the corresponding distribution observed in the server layer. The two distributions can be characterized by Zipf-like distributions and ?, the degree of disparity in the popularity distribution, is calculated for both. In all cases ? is higher to one implying a huge concentration of popularity on a few objects

Measurement-driven temporal analysis of information diffusion in online social networks

The rapid development of online social networks (OSN) renders them a popular mechanism for information diffusion. Studying the temporal characteristics is critical in understanding the diffusion process. However, due to the lack of well-defined propagation data, hardly any study addresses the temporal feature of information diffusion in OSN. In this paper, we present a measurement study on information diffusion in the Renren social network. We investigate the latency of information propagation along social links and define the 'activation time' for an OSN user, and find that the activation time follows the lognormal distribution. Based on this, we develop two new information diffusion models incorporating asynchronous activation times. Application of the models in the influence maximization problem shows that they capture the temporal diffusion behavior very well. This leads to fundamental ramifications to many related OSN applications. © 2012 IEEE.published_or_final_versio

Scholarometer: A Social Framework for Analyzing Impact across Disciplines

The use of quantitative metrics to gauge the impact of scholarly publications, authors, and disciplines is predicated on the availability of reliable usage and annotation data. Citation and download counts are widely available from digital libraries. However, current annotation systems rely on proprietary labels, refer to journals but not articles or authors, and are manually curated. To address these limitations, we propose a social framework based on crowdsourced annotations of scholars, designed to keep up with the rapidly evolving disciplinary and interdisciplinary landscape. We describe a system called Scholarometer, which provides a service to scholars by computing citation-based impact measures. This creates an incentive for users to provide disciplinary annotations of authors, which in turn can be used to compute disciplinary metrics. We first present the system architecture and several heuristics to deal with noisy bibliographic and annotation data. We report on data sharing and interactive visualization services enabled by Scholarometer. Usage statistics, illustrating the data collected and shared through the framework, suggest that the proposed crowdsourcing approach can be successful. Secondly, we illustrate how the disciplinary bibliometric indicators elicited by Scholarometer allow us to implement for the first time a universal impact measure proposed in the literature. Our evaluation suggests that this metric provides an effective means for comparing scholarly impact across disciplinary boundaries. © 2012 Kaur et al