Characterizing popularity dynamics of online videos

Ren, Zhuo-Ming; Shi, Yuqiang; Liao, Hao

doi:10.1016/j.physa.2016.02.019

Cited by 15 publications

(13 citation statements)

References 33 publications

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“…For example, in Ren et al [21], the authors point out that the online popularity is a significant effecting factor on videos in online systems; in Iveroth et al [22], competitors' price is a base factor for deciding; in Choi et al [23], they imply that discount on price can have effect on the sales of information goods; in another study, Niu and Li [24] suggest for the Internet service providers a price model depending on the congestion of Internet. (ii) Model validation: our time-continuous model should fit the data collected in real world, identify model coefficients, and validate other sets of data.…”

Section: Resultsmentioning

confidence: 99%

Two-Stage Dynamic Pricing and Advertising Strategies for Online Video Services

Tan

2017

Discrete Dynamics in Nature and Society

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As the demands for online video services increase intensively, the selection of business models has drawn the great attention of online providers. Among them, pay-per-view mode and advertising mode are two important resource modes, where the reasonable fee charge and suitable volume of ads need to be determined. This paper establishes an analytical framework studying the optimal dynamic pricing and advertising strategies for online providers; it shows how the strategies are influenced by the videos available time and the viewers' emotional factor. We create the two-stage strategy of revenue models involving a single fee mode and a mixed fee-free mode and find out the optimal fee charge and advertising level of online video services. According to the results, the optimal video price and ads volume dynamically vary over time. The viewer's aversion level to advertising has direct effects on both the volume of ads and the number of viewers who have selected low-quality content. The optimal volume of ads decreases with the increase of ads-aversion coefficient, while increasing as the quality of videos increases. The results also indicate that, in the long run, a pure fee mode or free mode is the optimal strategy for online providers.

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Section: Resultsmentioning

confidence: 99%

Two-Stage Dynamic Pricing and Advertising Strategies for Online Video Services

Tan

2017

Discrete Dynamics in Nature and Society

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“…And our results also show that the users' choice of different types of online contents are not only affected by a simply factor, thus considering the different properties among different populations, and analyzing separately if possible are necessary for accurate prediction of the growth. However, on the one hand, we would enhance our model to regenerate the long-term popularity of online objects [37] and consider more popularity mechanisms from the perspective of social system in our future works, such as community [38][39][40], trust relationship, and friend relationship, and so on. On the other hand, the potential factors on Apps' becoming popular is still a meaningful field to improve the popularity of online objects.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Uncovering the popularity mechanisms for Facebook applications

Guo

Yang

et al. 2018

Physica A: Statistical Mechanics and its Applications

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h i g h l i g h t s• For different kinds of Facebook Apps and found that the recent and cumulative popularity play important roles.• We present a model to regenerate the growth of popularity for different App groups.• The recent popularity plays more important role in regenerating the popularity dynamics for more popular Apps.• The cumulative popularity plays more important role for unpopular Apps.Understanding the popularity dynamics of online application(App) is significant for the online social systems. In this paper, by dividing the Facebook Apps into different groups in terms of their popularities, we empirically investigate the popularity dynamics for different kinds of Facebook Apps. Then, taking into account the influence of cumulative and recent popularities on the user choice, we present a model to regenerate the growth of popularity for different App groups. The experimental results of 917 Facebook Apps show that as the popularities of Facebook Apps increase, the recent popularity plays more important role. Specifically, the recent popularity plays more important role in regenerating the popularity dynamics for more popular Apps, and the cumulative popularity plays more important role for unpopular Apps. We also conduct temporal analysis on the growth characteristic of individual App by comparing the increment at each time with the average of historical records. The results show that the growth of more popular App tends to fluctuate more greatly. Our work may shed some lights for deeply understanding the popularity mechanism for online applications.

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“…Degree Increase (DI): The time information is often overlooked in the evolution of complex networks. In fact, time plays a crucial role in the evolution of information networks [31,32,33]. The combination of recommendation systems with time dynamics improve the recommendation and allows to perform better predictions.…”

Section: Recommendation Systemmentioning

confidence: 99%

Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network

Liao

Huang

et al. 2018

Complexity

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A PREPRINT -APRIL 5, 2019 Prediction is one of the major challenges in complex systems. The prediction methods have shown to be effective predictors of the evolution of networks. These methods can help policy makers to solve practical problems successfully and make better strategy for the future. In this work, we focus on exporting countries' data of the international trading network. A recommendation system is then used to identify the products corresponding to the production capacity of each individual country, but are somehow overlook by the country. Then, we simulate the evolution of the country's fitness if it would have followed the recommendations. The result of this work is the combination combine these two methods to provide insights to countries on how to enhance the diversification of their exported products in a scientific way and improve national competitiveness significantly, especially for developing countries. IntroductionInternational trade plays a considerable role in the exchange channels between countries [1,2]. It is also becoming more important as time goes on. In 1960, international trade accounted for roughly 25% of a country's total Gross Domestic Product (GDP). Nowadays it accounts for nearly 60% of countries GDP [3]. Historically, various classic economic models were developed to evaluate the dissimilarity of wealth that result from the exportation of diverse goods [4]. Models based on the gravity equation were also developed and showed to be adequate to explain many of the features of the international trade [5]. Another approach, The Product Space, attempted to illustrate how the nations will develop in the future by projecting the exports data onto a two-dimensional map and observing the diffusion of the export process [6]. Economic models mainly consist of commodity profits, geographical relations, comprehensive productivity, economic structure [7] and a series of macroeconomic elements. In practice, numerous complex external factors e.g. national policies, religious beliefs and the country's current production capacity, are key components in the international trade. Here, we also recognize that plenty of sociologists have constructed grand theories on the empirical study of Global Economic Development [8,9,10]. These methods and theories were developed by David Snyder, and Edward L. Kick [11], it was the first study of international trade and world economic growth using a network framework in American journal of sociology 1979. In Ref. [12], the authors emphasized on the importance of the global trade, and the structure of modern world system were addressed by multiple-network analysis. The complex network approach was also used in [13], and it was shown that the international trade network and the World Wide Web both have collaborative characteristics [14]. Indeed, the international trade network is a complex network in terms of structure. With this is in mind, we apply recommendation algorithms that are usually applied on e-commerce systems in order to predict the evolution of...

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Characterizing popularity dynamics of online videos

Cited by 15 publications

References 33 publications

Two-Stage Dynamic Pricing and Advertising Strategies for Online Video Services

Two-Stage Dynamic Pricing and Advertising Strategies for Online Video Services

Uncovering the popularity mechanisms for Facebook applications

Enhancing Countries’ Fitness with Recommender Systems on the International Trade Network

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