Multiple bursts of highly retweeted articles on social media

Renmeng Cao, Xianwen Wang (), Xiaoke Xu () and Jianlin Zhou
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Renmeng Cao: Dalian University of Technology
Xianwen Wang: Dalian University of Technology
Xiaoke Xu: Dalian Minzu University
Jianlin Zhou: China University of Geosciences (Beijing)

Scientometrics, 2021, vol. 126, issue 6, No 27, 5165-5179

Abstract: Abstract In this study, we perform a diachronic analysis of the temporal trends of scholarly articles over a fairly long time scale. Through the retweeting dynamics of 298 highly retweeted articles, we find that nearly 57% of the articles have multiple peaks on diffusion curves after their initial exposure on social media. We characterize this phenomenon by measuring the time interval between peaks, the height and width of peaks, diffusion performance and the similarities between peaks. We discover that bursts of multi-peak articles usually have short durations and small coverage and that the length of the peak interval determines correlations between peaks. We also find that overlapping users between peaks can act like weak ties and spread information from one group to another, catalyzing information to experience a renewed burst of retweets. Based on the presence or absence of overlapping users, we summarize the occurrence mechanism of the multi-peak phenomenon into two types: (1) Cross-community diffusion through overlapping users. (2) Bursty diffusion of key opinion leaders at different times.

Keywords: Altmetrics; Social media; Twitter; Complex network analysis; Multiple bursts; Weak ties (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11192-021-03970-7

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