## 2 Methods
### Data Collection and Cleaning  
The research was conducted using ethical guidelines established by the JEthics Committee for Research Involving Human Subjects at Universiti Putra Malaysia (JKEUPM) [Ref. No.: 2023-1338]. Data utilized in this study were sourced from textual content (reviews)  
Figure 1: The urban section of Hutuo River Corridor in Shijiazhuang (Zhonghua Avenue–North Extension of East Third Road).  
Figure 2: Social media data processing flowchart.  
available on Dianping (v.11.17.4), a prominent local life information provider and online rating platform in China. Dianping holds the second position in monthly active users according to the \"2022 China's Top 10 Lifestyle and Leisure App Monthly Active Users Ranking\" report [54], boasting a substantial user base spanning diverse socioeconomic backgrounds and age groups. All data collected from Dianping were voluntary submissions by users and publicly available, devoid of personally identifiable information. Consequently, users implicitly consented to using their data for research upon registering on the platform. The absence of encryption facilitated efficient data cleaning and analysis, supporting the extraction of valuable insights through algorithms. The utilization of Dianping data aligns with China's regulations governing data usage for academic research. Given the platform's representativeness, open-source nature, cost-free availability, and widespread usage across social media platforms, it emerged as the preferred source for foundational data in this study.  
During the data collection process, measures were implemented to safeguard against the inclusion of sensitive or identifying information. Data were securely stored and accessible solely to authorized researchers. Users' comments underwent anonymization prior to analysis to ensure privacy and confidentiality. The final collected data structure encompasses the following variables: user nickname, comment content, review timestamp, and scenic spot name.  
During data collection, it is possible to encounter dirty, noisy, or missing data. Therefore, performing preliminary cleaning while collecting the data, then the dataset was exported to Excel after collection completion, and multiple rounds of manual cleaning were performed based on the following principles:  
1. Exclusion of garbled data, such as emoticons or web links embedded within comments.
2. Removal of meaningless characters like \"##%....Y#!!Y(\"&\".
3. Elimination of duplicate data, where if a data entry appears more than once, only one instance is retained.
4. Removal of invalid reviews, defined as those containing fewer than five characters or consisting solely of emoticon symbols such as \"like\", \"good\", or \"okay\".
5. Elimination of data redundancy, excluding repetitive content within reviews, such as \"good, good, good\", \"not bad, not bad, not bad\", \"like like like\", and \"recommend, recommend, recommend\".  
Given the revitalization and improvement of the Hutuo River (urban section of Shijiazhuang) that occurred after 2017, the data collection period spans from 1 January 2017, to 31 December 2023. After multiple meticulous cleaning, a total of 3006 valid review entries for the Hutuo River Corridor (urban section of Shijiazhuang) were obtained.