Three-step Algorithms for Detection of High Degree Nodes in Online Social Networks

Авторы: Shaikhelislamov D., Drobyshevskiy M., Turdakov D., Yatskov A., Varlamov M., Aivazov D.
Сборник: 2020 Ivannikov Memorial Workshop
Год издания: 2020
Первая страница: 43
Последняя страница: 48
DOI: 10.1109/IVMEM51402.2020.00014
Аннотация: his paper considers the problem of influential users detection in online social networks. Identifying of such key entities is of interest in many areas: marketing, politics, information security, business. The degree of the node of the corresponding graph is used as a popularity indicator in this work. Network query limitation is the main challenge in discovering their structure. Therefore, our task is to detect a percentage of the highest degree network nodes under a budget restriction. We propose a three-step crawling algorithm in two versions to solve the problem. We experimentally show its efficiency at various budget limits and superiority over known crawling strategies. For example, to detect top-1% of hubs with 90% precision, one needs to crawl 5% of graph nodes in average with our 3-StepBatch algorithm. We also show that our algorithm performs well for different target set sizes, from 0.01% to 10% of the graph.
Добавил в систему: Турдаков Денис Юрьевич

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