It is widely believed that information spread on social media is a percolation process, with parallels to phase transitions in theoretical physics. However, evidence for this hypothesis is limited, as phase transitions have not been directly observed in any social media. Here, through analysis of 100 million Weibo and 40 million Twitter users, we identify percolation-like spread, and find that it happens more readily than current theoretical models would predict. The lower percolation threshold can be explained by the existence of positive feedback in the coevolution between network structure and user activity level, such that more active users gain more followers. Moreover, this coevolution induces an extreme imbalance in users' influence. Our findings indicate that the ability of information to spread across social networks is higher than expected, with implications for many information spread problems.
Epidemic extinction requires substantial resources over the period of outbreak. It is crucial to have an efficient strategy to assign resources due to the limited budget. In this paper, on the basis of epidemic spreading model proposed in [Chen et al., PRE, 2019], we investigate how to allocate resources in different periods of epidemics. Our results show that due to the resource moderately concentrated during the period of outbreak, the epidemics become extinct with much fewer resources. Specifically, we found that the optimal devoted resource strategy saves total devoted resource several times. This study is helpful to understand the impact of devoted resources on epidemic extinction and to design epidemic strategies under limited budget.
Preferences or dislikes for specific numbers are ubiquitous in human society. In traditional Chinese culture, people show special preference for some numbers, such as 6, 8, 10, 100, 200, etc. By analyzing the data of 6.8 million users of Sina Weibo, one of the largest online social media platforms in China, we discover that users exhibit a distinct preference for the number 200, i.e., a significant fraction of users prefer to follow 200 friends. This number, which is very close to the Dunbar number that predicts the cognitive limit on the number of stable social relationships, motivates us to investigate how the preference for numbers in traditional Chinese culture is reflected on social media. We systematically portray users who prefer 200 friends and analyze their several important social features, including activity, popularity, attention tendency, regional distribution, economic level, and education level. We find that the activity and popularity of users with the preference for the number 200 are relatively lower than others. They are more inclined to follow popular users, and their social portraits change relatively slowly. Besides, users who have a stronger preference for the number 200 are more likely to be located in regions with underdeveloped economies and education. That indicates users with the preference for the number 200 are likely to be vulnerable groups in society and are easily affected by opinion leaders.
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