{"title":"基于文本挖掘和GIS的主题公园游客情感分析的地理空间和社会媒体分析","authors":"Dr. S. Manoharan, Prof. Sathish","doi":"10.36548/jitdw.2020.2.003","DOIUrl":null,"url":null,"abstract":"Scrutinizing the emotions of customers and social media analytics are gaining popularity in the recent days. However, analysis of the emotions of visitors in theme parks are done on a lesser scale. In this paper, based on social media messages, the emotions of the visitors of a theme park is analyzed using geospatial as well as social media analytics convergence and visualization of cohesive places where expressions are gathered. Based on the Russell’s Circumplex Model of Affect, the words and emotions are analyzed in around 50,000 tweets collected of which 20,400 tweets contained one or more such words. Analysis of exploratory spatial data based on GIS and analysis of text mining represents various emotion in each quadrant based on the tweets. The visitor emotions are associated to various topics and emotions of considerable spatial variations. Based on the significant clustering of emotions in each quadrant, the areas of riding attraction in the theme park are identified and displayed using this research approach. Based on the analysis and implications of this research work, it is possible to develop ways in which the pleasant emotions of the visitors can be evoked by practitioners.","PeriodicalId":299307,"journal":{"name":"June 2020","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Geospatial and Social Media Analytics for Emotion Analysis of Theme Park Visitors using Text Mining and GIS\",\"authors\":\"Dr. S. Manoharan, Prof. Sathish\",\"doi\":\"10.36548/jitdw.2020.2.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scrutinizing the emotions of customers and social media analytics are gaining popularity in the recent days. However, analysis of the emotions of visitors in theme parks are done on a lesser scale. In this paper, based on social media messages, the emotions of the visitors of a theme park is analyzed using geospatial as well as social media analytics convergence and visualization of cohesive places where expressions are gathered. Based on the Russell’s Circumplex Model of Affect, the words and emotions are analyzed in around 50,000 tweets collected of which 20,400 tweets contained one or more such words. Analysis of exploratory spatial data based on GIS and analysis of text mining represents various emotion in each quadrant based on the tweets. The visitor emotions are associated to various topics and emotions of considerable spatial variations. Based on the significant clustering of emotions in each quadrant, the areas of riding attraction in the theme park are identified and displayed using this research approach. Based on the analysis and implications of this research work, it is possible to develop ways in which the pleasant emotions of the visitors can be evoked by practitioners.\",\"PeriodicalId\":299307,\"journal\":{\"name\":\"June 2020\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"June 2020\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36548/jitdw.2020.2.003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"June 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36548/jitdw.2020.2.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32
摘要
最近,仔细观察顾客的情绪和社交媒体分析越来越受欢迎。然而,对主题公园游客情绪的分析规模较小。本文以社交媒体信息为基础,利用地理空间分析和社交媒体分析对主题公园游客的情感进行分析,并对聚集表达的凝聚力场所进行融合和可视化。基于Russell 's Circumplex Model of Affect,研究人员对收集到的约5万条推文中的词语和情绪进行了分析,其中20400条推文包含一个或多个这样的词语。基于GIS的探索性空间数据分析和基于推文的文本挖掘分析代表了每个象限的各种情感。游客的情绪与各种主题和情绪有很大的空间差异。基于每个象限情感的显著聚类,利用该研究方法对主题公园的游乐景点区域进行识别和展示。基于本研究工作的分析和启示,我们有可能开发出实践者能够唤起来访者愉悦情绪的方法。
Geospatial and Social Media Analytics for Emotion Analysis of Theme Park Visitors using Text Mining and GIS
Scrutinizing the emotions of customers and social media analytics are gaining popularity in the recent days. However, analysis of the emotions of visitors in theme parks are done on a lesser scale. In this paper, based on social media messages, the emotions of the visitors of a theme park is analyzed using geospatial as well as social media analytics convergence and visualization of cohesive places where expressions are gathered. Based on the Russell’s Circumplex Model of Affect, the words and emotions are analyzed in around 50,000 tweets collected of which 20,400 tweets contained one or more such words. Analysis of exploratory spatial data based on GIS and analysis of text mining represents various emotion in each quadrant based on the tweets. The visitor emotions are associated to various topics and emotions of considerable spatial variations. Based on the significant clustering of emotions in each quadrant, the areas of riding attraction in the theme park are identified and displayed using this research approach. Based on the analysis and implications of this research work, it is possible to develop ways in which the pleasant emotions of the visitors can be evoked by practitioners.