Measurement and analysis on microblog network of emergency topic

Wang, Zhuo; Lei, Youxun; Yang, Tan

doi:10.1109/icnc.2014.6975945

Cited by 2 publications

(2 citation statements)

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“…So this paper adopts linear threshold model. In order to make the model conform to the real world as much as possible, we analyze the characteristics of the bursty events in social network [25]. The microblog influence calculation model proposed in this paper is shown in Figure 1.…”

Section: Detection Methods a Key Microblog Computing Modelmentioning

confidence: 99%

Sina Weibo Bursty Event Detection Method

Chen

Liang

2019

IEEE Access

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In response to the recent frequent outbreaks of bursty events, if the supervision is not strengthened, the grievances caused by it will have an extremely negative impact on society. Therefore, how to effectively detect bursty events in social networks has become the focus of research. In order to eliminate the interference of local daily events generated by noisy data, this paper proposes a bursty event detection method for quantifying the influence of microblog text. Through the analysis of high-impact microblogs, the burst words are mined, the potential bursty event data sets are constructed, and the k-means cluster analysis method is applied to detect the event. In order to verify the method, this paper compares with the commonly used detection methods on the real dataset. The experimental results show that the method has certain improvement in accuracy and efficiency.

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Section: Detection Methods a Key Microblog Computing Modelmentioning

confidence: 99%

Sina Weibo Bursty Event Detection Method

Chen

Liang

2019

IEEE Access

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“…Samuel et al [32] identified public sentiment amid problematic socioeconomic consequences of the lockdown during COVID-19, and explored ensuing four potential public sentiment associated scenarios. Wang et al [33] measured topological characteristics of emergency transmission in the microblog, and found that the network of emergency topic had small-world properties. An et al [34] identified salient topic categories and outlined their evolution patterns and temporal trends in microblogs on a public health emergency across different stages.…”

Section: Research On Users' Behaviours In Emergency Eventsmentioning

confidence: 99%

Detecting the public’s information behaviour preferences in multiple emergency events

Zhou

2021

Journal of Information Science

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Due to the frequent occurrence of public emergency events and the extensive use of social media in recent years, the public is more and more involved in the communication of public emergencies. As important members of the public, the rapid and massive information sharing of social media users makes them play an increasingly crucial role in the emergency processing. Hence, it is necessary to analyse information behaviours of social media users in emergency events. This article mined the information behaviours of users in multiple events to reflect the public’s behaviour preferences, aiming to provide information support for emergency handling. Specifically, we collected the user-generated contents related to emergency events, and then analysed the user-generated contents from multiple dimensions to obtain the corresponding information behaviours. Finally, based on the comparative analysis of four events, the information behaviour preferences of the public during emergencies were obtained. The experimental results indicate that the public’s behaviours in emergencies are related to their own interests and economic status, and curiosity about the details of events is the consistent appeal of the public.

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Measurement and analysis on microblog network of emergency topic

Cited by 2 publications

References 1 publication

Sina Weibo Bursty Event Detection Method

Sina Weibo Bursty Event Detection Method

Detecting the public’s information behaviour preferences in multiple emergency events

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