Panos Kostakos, Somkiadcharoen Robroo, Bofan Lin, M. Oussalah
{"title":"利用酒店评论预测犯罪?","authors":"Panos Kostakos, Somkiadcharoen Robroo, Bofan Lin, M. Oussalah","doi":"10.1109/EISIC49498.2019.9108861","DOIUrl":null,"url":null,"abstract":"Can hotel reviews be used as a proxy for predicting crime hotspots? Domain knowledge indicates that hotels are crime attractors, and therefore, hotel guests might be reliable “human crime sensors”. In order to assess this heuristic, we propose a novel method by mapping actual crime events into hotel reviews from London, using spatial clustering and sentiment feedback. Preliminary findings indicate that sentiment scores from hotel reviews are inversely correlated with crime intensity. Hotels with positive reviews are more likely to be adjacent to crime hotspots, and vice versa. One possible explanation for this counterintuitive finding that the review data are not mapped against specific crime types, and thus the crime data capture mostly police visibility on the site. More research and domain knowledge are needed to establish the strength of hotel reviews as a proxy for crime prediction.","PeriodicalId":117256,"journal":{"name":"2019 European Intelligence and Security Informatics Conference (EISIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Crime Prediction Using Hotel Reviews?\",\"authors\":\"Panos Kostakos, Somkiadcharoen Robroo, Bofan Lin, M. Oussalah\",\"doi\":\"10.1109/EISIC49498.2019.9108861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Can hotel reviews be used as a proxy for predicting crime hotspots? Domain knowledge indicates that hotels are crime attractors, and therefore, hotel guests might be reliable “human crime sensors”. In order to assess this heuristic, we propose a novel method by mapping actual crime events into hotel reviews from London, using spatial clustering and sentiment feedback. Preliminary findings indicate that sentiment scores from hotel reviews are inversely correlated with crime intensity. Hotels with positive reviews are more likely to be adjacent to crime hotspots, and vice versa. One possible explanation for this counterintuitive finding that the review data are not mapped against specific crime types, and thus the crime data capture mostly police visibility on the site. More research and domain knowledge are needed to establish the strength of hotel reviews as a proxy for crime prediction.\",\"PeriodicalId\":117256,\"journal\":{\"name\":\"2019 European Intelligence and Security Informatics Conference (EISIC)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 European Intelligence and Security Informatics Conference (EISIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EISIC49498.2019.9108861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 European Intelligence and Security Informatics Conference (EISIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EISIC49498.2019.9108861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Can hotel reviews be used as a proxy for predicting crime hotspots? Domain knowledge indicates that hotels are crime attractors, and therefore, hotel guests might be reliable “human crime sensors”. In order to assess this heuristic, we propose a novel method by mapping actual crime events into hotel reviews from London, using spatial clustering and sentiment feedback. Preliminary findings indicate that sentiment scores from hotel reviews are inversely correlated with crime intensity. Hotels with positive reviews are more likely to be adjacent to crime hotspots, and vice versa. One possible explanation for this counterintuitive finding that the review data are not mapped against specific crime types, and thus the crime data capture mostly police visibility on the site. More research and domain knowledge are needed to establish the strength of hotel reviews as a proxy for crime prediction.