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无障碍环境:通过在线评论为包容性城市设计提供众包方法","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":"arxiv-2409.08459","DOIUrl":null,"url":null,"abstract":"As urban populations grow, the need for accessible urban design has become\nurgent. Traditional survey methods for assessing public perceptions of\naccessibility are often limited in scope. Crowdsourcing via online reviews\noffers a valuable alternative to understanding public perceptions, and\nadvancements in large language models can facilitate their use. This study uses\nGoogle Maps reviews across the United States and fine-tunes Llama 3 model with\nthe Low-Rank Adaptation technique to analyze public sentiment on accessibility.\nAt the POI level, most categories -- restaurants, retail, hotels, and\nhealthcare -- show negative sentiments. Socio-spatial analysis reveals that\nareas with higher proportions of white residents and greater socioeconomic\nstatus report more positive sentiment, while areas with more elderly,\nhighly-educated residents exhibit more negative sentiment. Interestingly, no\nclear link is found between the presence of disabilities and public sentiments.\nOverall, this study highlights the potential of crowdsourcing for identifying\naccessibility challenges and providing insights for urban planners.","PeriodicalId":501032,"journal":{"name":"arXiv - CS - Social and Information Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","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\":\"arxiv-2409.08459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As urban populations grow, the need for accessible urban design has become\\nurgent. Traditional survey methods for assessing public perceptions of\\naccessibility are often limited in scope. Crowdsourcing via online reviews\\noffers a valuable alternative to understanding public perceptions, and\\nadvancements in large language models can facilitate their use. This study uses\\nGoogle Maps reviews across the United States and fine-tunes Llama 3 model with\\nthe Low-Rank Adaptation technique to analyze public sentiment on accessibility.\\nAt the POI level, most categories -- restaurants, retail, hotels, and\\nhealthcare -- show negative sentiments. Socio-spatial analysis reveals that\\nareas with higher proportions of white residents and greater socioeconomic\\nstatus report more positive sentiment, while areas with more elderly,\\nhighly-educated residents exhibit more negative sentiment. Interestingly, no\\nclear link is found between the presence of disabilities and public sentiments.\\nOverall, this study highlights the potential of crowdsourcing for identifying\\naccessibility challenges and providing insights for urban planners.\",\"PeriodicalId\":501032,\"journal\":{\"name\":\"arXiv - CS - Social and Information Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Social and Information Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08459\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Social and Information Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","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 survey methods for assessing public perceptions of
accessibility are often limited in scope. Crowdsourcing via online reviews
offers a valuable alternative to understanding public perceptions, and
advancements in large language models can facilitate their use. This study uses
Google Maps reviews across the United States and fine-tunes Llama 3 model with
the Low-Rank Adaptation technique to analyze public sentiment on accessibility.
At the POI level, most categories -- restaurants, retail, hotels, and
healthcare -- show negative sentiments. Socio-spatial analysis reveals that
areas with higher proportions of white residents and greater socioeconomic
status report more positive sentiment, while areas with more elderly,
highly-educated residents exhibit more negative sentiment. Interestingly, no
clear link is found between the presence of disabilities and public sentiments.
Overall, this study highlights the potential of crowdsourcing for identifying
accessibility challenges and providing insights for urban planners.