论文标题
征服：单一分数的共识情感审查分析和平台评分
ConTrip: Consensus Sentiment review Analysis and Platform ratings in a single score
论文作者
论文摘要
人们明确地采用评论来决定购买商品或互联网上的体验。在这方面，越来越多的意义和意见数量导致了自动评估其情感内容的方法的发展。但是，模型创建共识值并不是一件直接的，该价值体现了不同评论的一致性，并区分了项目的均等评分。基于Nguyen等人提出的方法。在2020年，我们得出了一个名为Contrip的新颖共识值，该价值将其共识分数和一个平台的整体评分融合在一起。互联在于评级范围值，这使其更容易解释，同时保持在跨评级体验之间进行区分的能力。在https://github.com/pepebonet/contripscore上实施并在MIT许可证下实施并免费提供契合。
People unequivocally employ reviews to decide on purchasing an item or an experience on the internet. In that regard, the growing significance and number of opinions have led to the development of methods to assess their sentiment content automatically. However, it is not straightforward for the models to create a consensus value that embodies the agreement of the different reviews and differentiates across equal ratings for an item. Based on the approach proposed by Nguyen et al. in 2020, we derive a novel consensus value named ConTrip that merges their consensus score and the overall rating of a platform for an item. ConTrip lies in the rating range values, which makes it more interpretable while maintaining the ability to differentiate across equally rated experiences. ConTrip is implemented and freely available under MIT license at https://github.com/pepebonet/contripscore
