Multi-lingual opinion mining on YouTube
作者：
Highlights：
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• We designed the first model for effectively carrying out opinion mining on YouTube comments.
• We propose kernel methods applied to a robust shallow syntactic structure, which improves accuracy for both languages.
• Our approach greatly outperforms other basic models on cross-domain settings.
• We created a YouTube corpus (in Italian and English) and made it available for the research community.
• Comments must be classified in subcategories to make opinion mining effective on YouTube.
摘要
•We designed the first model for effectively carrying out opinion mining on YouTube comments.•We propose kernel methods applied to a robust shallow syntactic structure, which improves accuracy for both languages.•Our approach greatly outperforms other basic models on cross-domain settings.•We created a YouTube corpus (in Italian and English) and made it available for the research community.•Comments must be classified in subcategories to make opinion mining effective on YouTube.
论文关键词：Natural Language Processing,Opinion mining,Social media
论文评审过程：Received 15 May 2014, Revised 4 February 2015, Accepted 8 March 2015, Available online 9 April 2015, Version of Record 10 December 2015.
论文官网地址：https://doi.org/10.1016/j.ipm.2015.03.002
