Group 1 - The core viewpoint of the article is that Ctrip is implementing measures to combat malicious hotel reviews to promote higher quality and sustainable development in the hotel industry [1] - Ctrip's Vice President highlighted the growing influence of online reviews and the emergence of "professional negative reviewers" who disrupt fair competition and affect the credibility of genuine user feedback [1] - Ctrip encourages hotels to proactively report suspicious behaviors, allowing them to refuse extortion attempts and ensuring that malicious reviews do not count towards the hotel's overall rating [1] Group 2 - Ctrip will fully upgrade its hotel review governance mechanism starting October 22, focusing on combating malicious reviews and extortion by professional negative reviewers [1] - The application of AI technology in identifying and defining malicious reviews involves analyzing hotel reports in conjunction with multidimensional data from the platform, including order characteristics and related complaint features [2] - The AI system is designed to learn and identify abnormal and potentially malicious behavior patterns from vast amounts of data, focusing on concentrated and high-frequency abnormal review patterns [2]

Core Viewpoint - The article discusses the measures taken by Meituan's "Pinh Hao Fan" to combat unreasonable and malicious reviews from consumers, which have been a significant issue for small and medium-sized restaurant owners. The platform has implemented various strategies to protect merchants' rights and reduce the impact of such reviews on their ratings [1][5]. Group 1: Measures Against Malicious Reviews - In the first half of the year, "Pinh Hao Fan" launched a special campaign to address unreasonable and malicious reviews, resulting in a 30% decrease in the number of such reviews compared to the beginning of the year [1]. - The number of complaints from merchants regarding malicious review users dropped by 55.7% during the same period [1]. - The platform has implemented measures such as screening out malicious users' reviews, excluding delivery-related negative reviews from ratings, and limiting orders from malicious users [1][4]. Group 2: Optimization of Order Remark Function - "Pinh Hao Fan" has optimized the order remark function, allowing merchants to choose whether to enable it and set their own remark tags, thereby reducing unreasonable remarks that lead to negative reviews [2]. - Merchants have reported a significant decrease in unreasonable requests, such as demands for extra food or items outside the service range, which previously increased their costs [2]. Group 3: Data on Malicious User Interventions - The platform has utilized a risk control big data model to automatically identify and block malicious users who frequently leave negative reviews for the same merchant, successfully intercepting 68,000 instances of such users and blocking 150,000 malicious reviews in the first half of the year [4]. - A model has been established to identify high-risk users who attempt to extort restaurants through negative reviews, leading to restrictions on refunds and further review screening [5]. Group 4: Importance of Accurate Ratings - Accurate and genuine user ratings are crucial for merchants as they serve as important operational indicators, while for consumers, they help in assessing the quality of service and food from restaurants [5].