دانلود رایگان مقاله انگلیسی بررسی تمایل شرکت در اقدامات اشتراکی فضای مجازی: قانون 5% - الزویر 2018

Abstract

The Internet and Big data have become indispensable in people’s daily life. The whole participation spectrum of cyberspace collective actions contains four stages, such as Access, Browse, Participate, and Offline. There exist three transition probabilities within four stages. This paper focuses on the ratio (second transition probability) between numbers of browse and participate, which is defined as the participate propensity PBP. In the real world, amounts of browse (millions) and participation (tens of thousands) are huge, and they take on irregular distributions. However, it is discovered in this paper that this participate propensity is stable and takes on the regularity of 5‰, i.e. the participation propensity is slightly under 5‰ for most times, while sometimes it is slightly over 5‰. The empirical big data of 310 online collective actions are collected from a famous BBS (Tianya.cn) in China. This 5‰ rule not only holds true for the total 310 cases, but also for yearly, quarterly, and other subgroups. Furthermore, we check distributive traits of PBP. It is not normally distributed as it has longer right tails. It is verified by the empirical big data that the propensity follows the lognormal distribution, which is relatively robust in the total and subgroups of 310 cyberspace collective actions. Given the distributive regularity of the participate propensity PBP, its probability density function can be obtained. Combined with the known amount of browsers, big data prediction of participation would be possible.

5. Conclusions

and Discussions In equation (5), given the primary normal distribution of under 310 cases, we are able to inference or estimate the normal distribution of with more and more data (Big Data), using the observed parameter values such as the mean and standard deviation of  Once the normal distribution is known, the probability density function f can be obtained, which paves the way for big data prediction of participant in online collective actions [5, 8, 11, 13, 14, 15, 18]. The key application of p’s normal distribution is to predict the amount of participation, based on the number of browse for specific types of online collective actions.