Why are some social-media contents more popular than others? Opinion and association rules mining applied to virality patterns discovery
作者：
Highlights：
• A novel approach to extract virality patterns from social media Twitter is presented.
• Opinion mining extracts subjective content transforming it into structured data.
• Association rule mining is applied to structured data to extract virality patterns.
• Virality patterns were discovered for high share/likes and low share/likes.
• Extracted and relevant patterns were measured and analyzed.
摘要
•A novel approach to extract virality patterns from social media Twitter is presented.•Opinion mining extracts subjective content transforming it into structured data.•Association rule mining is applied to structured data to extract virality patterns.•Virality patterns were discovered for high share/likes and low share/likes.•Extracted and relevant patterns were measured and analyzed.
论文关键词：Natural language processing,Virality,Data mining,Association rules mining,Human language technologies,Opinion mining,Sentiment analysis
论文评审过程：Received 28 July 2021, Revised 2 December 2021, Accepted 11 February 2022, Available online 24 February 2022, Version of Record 26 February 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.116676
