ESAP: A novel approach for cross-platform event dissemination trend analysis between social network and search engine

Abstract

With the rapid development of Internet,new media,such as blogs,wikis,and social media,become a major platform for information dissemination. Numerous studies focus on event dissemination trend analysis for individual media platform,while very few works are conducted to study the dissemination characteristics in a cross-platform manner. In this work,we propose ESAP,a novel cross-platform approach to analyze the event dissemination trend between social network and search engine simultaneously. ESAP includes three models: an event popularity model based on hot word dynamic weight; a trend similarity model to measure the similarity of event popularity across different platforms over time; and an attention degree model to measure event public attention through time. Experimental results based on four real-world event dissemination datasets (two from Baidu and two from Weibo) produce several interesting findings and validate the effectiveness of ESAP in modeling and analyzing event dissemination trend between social network and search engine from different perspectives.