Characterizing popularity dynamics of hot topics using micro-blogs spatio-temporal data

Abstract

BackgroundWith the rapid development of mobile Internet technology, human society has entered an era of high interconnection between human and information. Especially the emergence of online social networks, such as Weibo in China, LinkedIn, Twitter, Face-book and so on, because of its high interaction and strong group participation, makes many related information converging and merging, leading to the emergence of hot topics on the Internet. These hot topics are the aggregation of information about current events (e.g., natural disasters, sports news, celebrity news), which have geotags-timestamp information. These metadata (geotags and timestamp) are embedded within the content of the message, so that the analysis of an event can be performed by applying a spacetime classification. In addition, the hot topic is the sprout of the network public opinion. Network public opinion has an important impact on the stability of the country and society. Therefore, the popularity of hot topics is studied from the spatial and temporal dimension can better understand the dissemination of public opinion. This paper uses the data of Sina Weibo, one of the largest micro-blogging system in China (https ://weibo .com/), to study the following two questions: (1) study the classification problem of hot topic on Weibo, cluster the popularity time series by clustering algorithm;(2) study the spatial distribution characteristics of hot topic on Weibo based on location label data. AbstractIn this paper, a quantitative temporal and spatial analysis of the dynamics of hot topics popularity in Micro-blogging system was provided. Firstly, the popularity time series of 1167 hot topics were counted and calculated by Excel. Secondly, based on MAT-LAB software,the popularity time series were clustered into six clusters by K-spectral centroid (K-SC) clustering algorithm. Thirdly, we analyzed temporal patterns and spatial patterns of popularity dynamics of topics by statistical methods. The results show that temporal popularity of micro-blogging topics is rapidly dying, and the distribution of popularity is subject to the power law form. In addition, most of the Micro-blogging topics are global topic. Our results can provide a literature reference for studying the influence of online hot topics and the evolution of public opinion. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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