Transportation sentiment analysis using word embedding and ontology-based topic modeling
作者：
Highlights：
• Social networks provide a new approach to collect data regarding transportation.
• Sentiment analysis can make observations of social data to examine transportation.
• Current text mining techniques are unable to generate the topics accurately.
• Document representation is another challenging tasks in sentiment analysis.
• We proposed a new topic modeling and word embedding system for sentiment analysis.
摘要
•Social networks provide a new approach to collect data regarding transportation.•Sentiment analysis can make observations of social data to examine transportation.•Current text mining techniques are unable to generate the topics accurately.•Document representation is another challenging tasks in sentiment analysis.•We proposed a new topic modeling and word embedding system for sentiment analysis.
论文关键词：Social network analysis,Sentiment analysis,Topic modeling,Mobility users,Word embedding
论文评审过程：Received 23 July 2018, Revised 2 January 2019, Accepted 24 February 2019, Available online 5 March 2019, Version of Record 18 April 2019.
论文官网地址：https://doi.org/10.1016/j.knosys.2019.02.033
