{"title":"Uncovering Los Angeles Tourists' Patterns Using Geospatial Analysis and Supervised Machine Learning with Random Forest Predictors","authors":"Yuan-Yuan Lee, Y. Chang","doi":"10.1109/CSCI49370.2019.00239","DOIUrl":null,"url":null,"abstract":"Consumer behavior analytics is at the epicenter of a Big Data revolution. In this paper we propose to analyze intra-regional spatial patterns mining tourists' behaviors and characteristics based on traveling group size with data collected from Airbnb open source focused on Los Angeles neighborhood in 2016. Random Forest Classification (RF) technique, an ensemble approach, is applied to identify the key drivers according to relevant traveler groups and presented patterns using Hotspot Analysis on Geographic Information System (GIS). Our empirical result highlights driving factors within Airbnb listings, providing valuable insights to better plan, monitor and manage tourism activity.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"18 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI49370.2019.00239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Consumer behavior analytics is at the epicenter of a Big Data revolution. In this paper we propose to analyze intra-regional spatial patterns mining tourists' behaviors and characteristics based on traveling group size with data collected from Airbnb open source focused on Los Angeles neighborhood in 2016. Random Forest Classification (RF) technique, an ensemble approach, is applied to identify the key drivers according to relevant traveler groups and presented patterns using Hotspot Analysis on Geographic Information System (GIS). Our empirical result highlights driving factors within Airbnb listings, providing valuable insights to better plan, monitor and manage tourism activity.