文献类型：期刊文献

英文题名：A 2020 perspective on Predicting the influence of viral messages for VM campaigns on Weibo

作者：Zhang, Yuqi[1];Li, Shugang[1];Yu, Zhaoxu[2];Zhang, Fangfang[1];Lu, Hanyu[1]

机构：[1]Shanghai Univ, Sch Management, Shanghai 200444, Peoples R China;[2]East China Univ Sci & Technol, Dept Automat, Shanghai 200237, Peoples R China

年份：2020

卷号：40

外文期刊名：ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS

收录：;EI(收录号：20200708165290);WOS:【SSCI(收录号:WOS:000528943600027)，SCI-EXPANDED(收录号:WOS:000528943600027)】；

基金：This work was supported by the Chinese National Natural Science Foundation (No. 71871135).

语种：英文

外文关键词：Data mining; Seeding strategies; Social networks; Viral marketing

摘要：Viral marketing (VM) in social networks (SNs) has the advantages of rapid distribution with comparatively little effort and is easy to reach the "hard-to-get" audience. Consequently, it has been being actively used by marketers to entice users and advertise products. The massive and diversified data in SNs presents opportunities to uncover the key to ensure the persistent and broad spread of a viral message, thus leading to successful VM campaigns. First, considering that a viral message is an integration of text, images, and videos, we concentrate on extracting significant features embedded in images and videos. Second, given that users often interact with each other and companies, the viral message may be enriched through its propagation. To accurately predict its influence, it is appropriate to account for the influence of the message itself and its derivatives. Third, identifying frequent interactions among users who have similar preferences or interests will contribute to well-targeted and effective VM campaigns.