Lingyao Li , Songhua Hu , Yinpei Dai , Min Deng , Parisa Momeni , Gabriel Laverghetta , Lizhou Fan , Zihui Ma , Xi Wang , Siyuan Ma , Jay Ligatti , Libby Hemphill
{"title":"实现令人满意的公共可达性:通过在线评论的众包方法来实现包容性城市设计","authors":"Lingyao Li , Songhua Hu , Yinpei Dai , Min Deng , Parisa Momeni , Gabriel Laverghetta , Lizhou Fan , Zihui Ma , Xi Wang , Siyuan Ma , Jay Ligatti , Libby Hemphill","doi":"10.1016/j.compenvurbsys.2025.102329","DOIUrl":null,"url":null,"abstract":"<div><div>As urban populations grow, the need for accessible urban design has become urgent. Traditional methods for assessing public perceptions of accessibility, such as surveys and interviews, are often resource-intensive and geographically limited in scope. Crowdsourcing via online reviews offers a valuable alternative to understanding public perceptions, and advancements in large language models (LLMs) can facilitate their use. In this study, we examine over one million Google Maps reviews from points of interests (POIs) across the United States and fine-tune the Llama 3 model using the Low-Rank Adaptation (LoRA) technique to identify public sentiment toward accessibility. At the POI level, most categories – restaurants, retail, hotels, and healthcare – show negative sentiments, indicating persistent barriers across key sectors. Socio-spatial regression analysis reveals that more positive sentiment is associated with areas that have higher proportions of white residents and greater socioeconomic advantage. Conversely, more negative sentiment is expressed in areas with higher concentrations of elderly and highly-educated populations. Interestingly, no clear link is found between the presence of disabilities and public sentiments, but a significant positive relationship does exist between disability-friendly scores and public perception. Overall, our findings demonstrate the value of crowdsourcing with LLM-enhanced analysis in identifying accessibility challenges and informing inclusive urban design, offering actionable insights for planners, policymakers, and advocates striving toward more equitable cities.</div></div>","PeriodicalId":48241,"journal":{"name":"Computers Environment and Urban Systems","volume":"122 ","pages":"Article 102329"},"PeriodicalIF":8.3000,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Toward satisfactory public accessibility: A crowdsourcing approach through online reviews to inclusive urban design\",\"authors\":\"Lingyao Li , Songhua Hu , Yinpei Dai , Min Deng , Parisa Momeni , Gabriel Laverghetta , Lizhou Fan , Zihui Ma , Xi Wang , Siyuan Ma , Jay Ligatti , Libby Hemphill\",\"doi\":\"10.1016/j.compenvurbsys.2025.102329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>As urban populations grow, the need for accessible urban design has become urgent. Traditional methods for assessing public perceptions of accessibility, such as surveys and interviews, are often resource-intensive and geographically limited in scope. Crowdsourcing via online reviews offers a valuable alternative to understanding public perceptions, and advancements in large language models (LLMs) can facilitate their use. In this study, we examine over one million Google Maps reviews from points of interests (POIs) across the United States and fine-tune the Llama 3 model using the Low-Rank Adaptation (LoRA) technique to identify public sentiment toward accessibility. At the POI level, most categories – restaurants, retail, hotels, and healthcare – show negative sentiments, indicating persistent barriers across key sectors. Socio-spatial regression analysis reveals that more positive sentiment is associated with areas that have higher proportions of white residents and greater socioeconomic advantage. Conversely, more negative sentiment is expressed in areas with higher concentrations of elderly and highly-educated populations. Interestingly, no clear link is found between the presence of disabilities and public sentiments, but a significant positive relationship does exist between disability-friendly scores and public perception. Overall, our findings demonstrate the value of crowdsourcing with LLM-enhanced analysis in identifying accessibility challenges and informing inclusive urban design, offering actionable insights for planners, policymakers, and advocates striving toward more equitable cities.</div></div>\",\"PeriodicalId\":48241,\"journal\":{\"name\":\"Computers Environment and Urban Systems\",\"volume\":\"122 \",\"pages\":\"Article 102329\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2025-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers Environment and Urban Systems\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0198971525000821\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers Environment and Urban Systems","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0198971525000821","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Toward satisfactory public accessibility: A crowdsourcing approach through online reviews to inclusive urban design
As urban populations grow, the need for accessible urban design has become urgent. Traditional methods for assessing public perceptions of accessibility, such as surveys and interviews, are often resource-intensive and geographically limited in scope. Crowdsourcing via online reviews offers a valuable alternative to understanding public perceptions, and advancements in large language models (LLMs) can facilitate their use. In this study, we examine over one million Google Maps reviews from points of interests (POIs) across the United States and fine-tune the Llama 3 model using the Low-Rank Adaptation (LoRA) technique to identify public sentiment toward accessibility. At the POI level, most categories – restaurants, retail, hotels, and healthcare – show negative sentiments, indicating persistent barriers across key sectors. Socio-spatial regression analysis reveals that more positive sentiment is associated with areas that have higher proportions of white residents and greater socioeconomic advantage. Conversely, more negative sentiment is expressed in areas with higher concentrations of elderly and highly-educated populations. Interestingly, no clear link is found between the presence of disabilities and public sentiments, but a significant positive relationship does exist between disability-friendly scores and public perception. Overall, our findings demonstrate the value of crowdsourcing with LLM-enhanced analysis in identifying accessibility challenges and informing inclusive urban design, offering actionable insights for planners, policymakers, and advocates striving toward more equitable cities.
期刊介绍:
Computers, Environment and Urban Systemsis an interdisciplinary journal publishing cutting-edge and innovative computer-based research on environmental and urban systems, that privileges the geospatial perspective. The journal welcomes original high quality scholarship of a theoretical, applied or technological nature, and provides a stimulating presentation of perspectives, research developments, overviews of important new technologies and uses of major computational, information-based, and visualization innovations. Applied and theoretical contributions demonstrate the scope of computer-based analysis fostering a better understanding of environmental and urban systems, their spatial scope and their dynamics.