This review explores the influence of soil-structure interaction (SSI) on the seismic response of structures, employing Latent Dirichlet Allocation (LDA) to identify research trends and thematic clusters. Key topics include the dynamic response of buildings, nonlinear modeling approaches, soil-foundation interaction, and performance-based seismic evaluation. SSI significantly modifies structural behavior, influencing vibration characteristics, wave propagation, and energy dissipation. Building parameters, soil stiffness, and foundation type were identified as critical factors impacting seismic performance. Advanced nonlinear modeling techniques, such as finite element analysis and optimization algorithms, have enhanced the accuracy of SSI simulations, enabling detailed assessments of soil-structure dynamics and damage probabilities. Innovations like gravel-rubber mixtures for seismic isolation and tuned mass dampers integrated with SSI were highlighted for their effectiveness in mitigating seismic impacts. The review highlights the necessity of incorporating SSI into design frameworks to address dynamic amplification, site-specific conditions, and fragility variations. However, critical gaps remain, particularly in large-scale fragility modeling, multi-hazard assessments, and experimental validations. These gaps highlight the need for further integration of SSI effects into seismic risk analyses and design codes. Future research should prioritize multi-disciplinary approaches that bridge theoretical advancements and practical applications to enhance structural resilience in seismically active regions. This study provides a comprehensive foundation for advancing SSI-informed seismic design practices and improving the safety and sustainability of infrastructure.

Glaciers are attracting increasing attention in the context of climate change, and glacier tourism has also become a popular tourist product. However, few studies have been conducted concerning the image of glacier tourism destinations. To address this gap in the literature, in this study, we extracted destination images from 138,709 visitor reviews of 107 glacier tourism destinations on TripAdvisor using latent Dirichlet allocation (LDA) topic modeling, identified destination image characteristics using salience-valence analysis (SVA), and analyzed the differences in glacier tourism destination image characteristics across seasons and regions. According to the findings, the image of a glacier tourism destination consists of 14 dimensions and 53 attributes, with landscapes and specific activities representing the core image and viewing location and necessity representing the unique image. We identified significant seasonal and regional differences in the image of glacier tourism destinations. Finally, we discussed the unique image of glacier tourism destinations, the reasons for differences in the images, and the characteristics of different glacier tourism regions. This research could assist in the scientific management of their core images by glacier tourism destinations, as well as in the rational selection of destinations and travel timing by glacier tourists.