Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events

Guan, Wanqiu; Gao, Haoyu; Yang, Ming; Li, Yuan; Ma, Haixin; Qian, Weining; Cao, Zhigang; Yang, Xiaoguang

doi:10.1016/j.physa.2013.09.059

Cited by 122 publications

(60 citation statements)

References 21 publications

(12 reference statements)

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“…Liu, Liu, and Li (2012) found that source trustworthiness, source expertise, source attractiveness, and the number of multimedia have significant effects on the information retweeting. Guan, Gao, and Yang (2014) found that male users are more likely to be involved in hot events, and messages that contain pictures and those posted by verified users are more likely to be retweet, while those with URLs are less likely. Lun, Peng, Zhang, Wang, and Zhu (2014) found that retweeting and commenting are distinct types of microblogging behaviors.…”

Section: Literature Reviewmentioning

confidence: 97%

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WITHDRAWN: The study on factors affecting the attraction of microblog

Song

2015

Computers in Human Behavior

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Section: Literature Reviewmentioning

confidence: 97%

“…The x t in the formulae (2.1) is calculated as: Liu et al (2012) and Guan et al (2014) measure microblog attraction with retweeting times. Lun et al (2014) use numbers of comments to measure microblog attraction.…”

Section: Data Collectionmentioning

confidence: 99%

WITHDRAWN: The study on factors affecting the attraction of microblog

Song

2015

Computers in Human Behavior

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“…The work [10] is concerned with 21 hot events which were widely discussed on Sina Weibo; it empirically analyzes their posting and reposting characteristics. In the work [2], by automatically identifying events and their associated user-contributed social media documents, the authors show how they can enable event browsing and search in a search engine.…”

Section: Related Workmentioning

confidence: 99%

Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week

Brambilla

Ceri

Daniel

et al. 2017

Lecture Notes in Computer Science

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Abstract. Social media response to catastrophic events, such as natural disasters or terrorist attacks, has received a lot of attention. However, social media are also extremely important in the context of planned events, such as fairs, exhibits, festivals, as they play an essential role in communicating them to fans, interest groups, and the general population. These kinds of events are geo-localized within a city or territory and are scheduled within a public calendar. We consider a specific scenario, the Milano Fashion Week (MFW), which is an important event in our city. We focus our attention on the spreading of social content in time, measuring the delay of the event propagation. We build different clusters of stakeholders (fashion brands), we characterize several features of time propagation and we correlate it to the popularity of involved actors. We show that the clusters by time and popularity are loosely correlated, and therefore the time response cannot be easily inferred. This motivates the development of a predictor through supervised learning in order to anticipate the space cluster of a new brand.

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“…[11] analyzed and compared user behaviors, including textural features, topics and sentiment polarity of micro-posts on two different microblogging platforms: Sina Weibo and Twitter. [12] discussed the posting and reposting characteristics of some hot events. However, so far there exists little knowledge about Chinese tourist's expectations and experiences in Switzerland from Weibo user behavior.…”

Section: User Generated Contentmentioning

confidence: 99%

Linked Data Based Framework for Tourism Decision Support System: Case Study of Chinese Tourists in Switzerland

Liu¹,

Calvé²,

Cretton³

et al. 2015

JCC

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Switzerland is one of the most desirable European destinations for Chinese tourists; therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leading social media platform-Sina Weibo, a hybrid of Twitter and Facebook-has more than 600 million users. Weibo's great market penetration suggests that tourism operators and markets need to understand how to build effective and sustainable communications on Chinese social media platforms. In order to offer a better decision support platform to tourism destination managers as well as Chinese tourists, we proposed a framework using linked data on Sina Weibo. Linked Data is a term referring to using the Internet to connect related data. We will show how it can be used and how ontology can be designed to include the users' context (e.g., GPS locations). Our framework will provide a good theoretical foundation for further understand Chinese tourists' expectation, experiences, behaviors and new trends in Switzerland.

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Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events

Cited by 122 publications

References 21 publications

WITHDRAWN: The study on factors affecting the attraction of microblog

WITHDRAWN: The study on factors affecting the attraction of microblog

Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week

Linked Data Based Framework for Tourism Decision Support System: Case Study of Chinese Tourists in Switzerland

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