Emergence of hashtag popularity on the Chinese microblog Sina Weibo
A new paper out in Physica A: Statistical Mechanics and its Applications by Hao Cui and János Kertész.
ABSTRACT / To understand the emergence of hashtag popularity in online social networking complex systems, we study the largest Chinese microblogging site Sina Weibo, which has a Hot Search List (HSL) showing in real time the ranking of the 50 most popular hashtags based on search activity. We investigate the prehistory of successful hashtags from 17 July 2020 to 17 September 2020 by mapping out the related interaction network preceding the selection to HSL. We have found that the circadian activity pattern has an impact on the time needed to get to the HSL. When analyzing this time we distinguish two extreme categories: (a) “Born in Rome”, which means hashtags are mostly first created by superhubs or reach superhubs at an early stage during their propagation and thus gain immediate wide attention from the broad public, and (b) “Sleeping Beauty”, meaning the hashtags gain little attention at the beginning and reach system-wide popularity after a considerable time lag. The evolution of the repost networks of successful hashtags before getting to the HSL show two types of growth patterns: “smooth” and “stepwise”. The former is usually dominated by a superhub and the latter results from consecutive waves of contributions of smaller hubs. The repost networks of unsuccessful hashtags exhibit a simple evolution pattern.