Who is Going to Help? Detecting Social Media Influencers to Spread Information About Missing Persons

Victor Stroele, Lorenza Leão Oliveira Moreno,Jorão Gomes, Thalita Thamires de Oliveira Silva,Enayat Rajabi, Jairo Francisco de Souza

IEEE Transactions on Technology and Society(2024)

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摘要
Although the disappearance of individuals is not a recent phenomenon, it remains a prevalent issue that inflicts significant emotional distress upon the families of the missing. Unfortunately, state action about this matter is lacking in several countries. One promising approach to address this problem involves appealing for information and reaching out to a wider network of individuals who may possess the ability to assist in locating the missing person. Social media platforms, such as Twitter, have proven to be particularly effective in disseminating information. However, the effectiveness of information dissemination is crucial to raise awareness within the community as a whole. This paper presents a method for identifying influential individuals on Twitter, with a focus on their geographic location, to maximize the diffusion of information about missing persons. Given the significance of the social circles and communities associated with the disappeared individuals, incorporating location data becomes an essential feature in the missing person domain. The contribution of this paper is threefold: (i) a novel method to identify location-aware influencers on Twitter based on an operational research model, (ii) an analysis of the information dissemination using publicly available missing person data collected from Brazilian non-governmental organizations and state websites, and (iii) a new missing person dataset that can serve as a valuable resource for further research.
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关键词
Influence maximization,Information dissemination,Mixed Integer Program,Missing persons,Social networks
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