An analytical model for information gathering and propagation in social networks using random graphs
作者：
Highlights：
• We propose a model for information gathering and propagation in social networks.
• We provide an analytical model for randomized node discovery in graphs.
• Applicable in advertising, recommendation system and crowdsourced database.
• We use the Erdos–Renyi model of the random graph to derive the analytical solution.
• The accuracy of our model is more than 95%.
摘要
•We propose a model for information gathering and propagation in social networks.•We provide an analytical model for randomized node discovery in graphs.•Applicable in advertising, recommendation system and crowdsourced database.•We use the Erdos–Renyi model of the random graph to derive the analytical solution.•The accuracy of our model is more than 95%.
论文关键词：Social networks,Data models,Information gathering,Data sharing,Business intelligence,Node discovery in graphs
论文评审过程：Received 16 July 2019, Revised 26 June 2020, Accepted 3 September 2020, Available online 8 September 2020, Version of Record 30 September 2020.
论文官网地址：https://doi.org/10.1016/j.datak.2020.101852
