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• W4387082814 abstract "Online Social Networks are built on relationships between individuals. Moreover, they are a space where particular events emerge more quickly than through traditional media such as newspapers or radio. These networks represent a good source for detecting indicators of changes, called weak signals, announcing future threats or opportunities for an organization. The identification of weak signals in a complex environment exposed to ongoing evolution is still a challenging task in research. This paper proposes an approach based on the topology of networks to identify weak signals. Our approach contrasts existing works that analyze significant themes and trends, i.e., strong signals prevalent in a social network at a particular time. We model social network data in the form of temporal interaction graphs. Then we choose graphlets (particular network motifs) as an operational tool to estimate the characteristics of weak signals. We demonstrate our approach accordingly by a study on retweets published in the last season of the TV series Game of Thrones, with which we evaluated and validated some properties of our approach." @default.
• W4387082814 created "2023-09-28" @default.
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• W4387082814 creator A5059589547 @default.
• W4387082814 date "2023-01-01" @default.
• W4387082814 modified "2023-09-28" @default.
• W4387082814 title "The Power of Weak Signals: A Twitter Analysis on Game of Thrones’ Final Season" @default.
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• W4387082814 doi "https://doi.org/10.1007/978-3-662-68100-8_2" @default.
• W4387082814 hasPublicationYear "2023" @default.
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