生成语法
计算机科学
质量(理念)
生成模型
生成设计
人工智能
质量评定
人机交互
工程类
运营管理
认识论
哲学
公制(单位)
作者
Guohou Shan,Shizhen Jia
标识
DOI:10.24251/hicss.2024.489
摘要
Online reviews matter for customers, firms, and platforms increasingly.The recent advancement of generative Artificial Intelligence (AI) techniques makes it possible to generate online reviews automatically.However, the relative impact of generative AI vs. humans on online review generation is unknown.On the one hand, generative AI can generate high quality reviews because they are trained on diverse and highquality data.On the other hand, generative AI hallucinates and may generate fabricated content, threatening the quality of the generated reviews.Using data from one of the biggest online review platforms, Yelp.com, we apply fixed effect models to understand the relative impact of generative AI vs. humans on the quality of generated reviews.We find that reviews from generative AI averagely have bigger ratings, a higher level of inconsistency between rating and sentiment, shorter, harder to read, and more positive and subjective content.Our study has both theoretical and practical implications.
科研通智能强力驱动
Strongly Powered by AbleSci AI