{"title":"基于情感分析的旅游网站评论游客意见分析","authors":"S. Amira, M. Irawan","doi":"10.12962/j20882033.v31i2.6338","DOIUrl":null,"url":null,"abstract":"Technology development nowadays makes it easier for people to access information. One of them is to find information regarding a place. Many prospective visitors would read reviews from people who have visited a place to find out how they rate a place. Opinion on other people’s reviews is very influential in influencing others’ decisions in assessing a place they want to visit. Opinion analysis can be done by conducting a sentiment analysis of hotel customer reviews. The data used are traveler reviews of hotels in East Java on the Tripadvisor site. Traveler reviews data was taken by crawling on tourist sites, and the unstructured reviews data would be a preprocessing and weighted term from reviews using the TF-IDF method. The classification process is done using the support vector machine method to find opinions from traveler reviews, which are positive or negative. Based on the classification results, hotels that have the most positive sentiments in Surabaya are Harris Hotel Gubeng and Pop! Hotel Gubeng with the same number of reviews, 252 reviews. In comparison, hotels with the most positive sentiment in Malang are Harris Hotel Malang with 311 reviews. The opinion analysis results are expected to help the hotel manager evaluate and develop to increase the number of tourist visits.","PeriodicalId":14549,"journal":{"name":"IPTEK: The Journal for Technology and Science","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Opinion Analysis of Traveler Based on Tourism Site Review Using Sentiment Analysis\",\"authors\":\"S. Amira, M. Irawan\",\"doi\":\"10.12962/j20882033.v31i2.6338\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Technology development nowadays makes it easier for people to access information. One of them is to find information regarding a place. Many prospective visitors would read reviews from people who have visited a place to find out how they rate a place. Opinion on other people’s reviews is very influential in influencing others’ decisions in assessing a place they want to visit. Opinion analysis can be done by conducting a sentiment analysis of hotel customer reviews. The data used are traveler reviews of hotels in East Java on the Tripadvisor site. Traveler reviews data was taken by crawling on tourist sites, and the unstructured reviews data would be a preprocessing and weighted term from reviews using the TF-IDF method. The classification process is done using the support vector machine method to find opinions from traveler reviews, which are positive or negative. Based on the classification results, hotels that have the most positive sentiments in Surabaya are Harris Hotel Gubeng and Pop! Hotel Gubeng with the same number of reviews, 252 reviews. In comparison, hotels with the most positive sentiment in Malang are Harris Hotel Malang with 311 reviews. The opinion analysis results are expected to help the hotel manager evaluate and develop to increase the number of tourist visits.\",\"PeriodicalId\":14549,\"journal\":{\"name\":\"IPTEK: The Journal for Technology and Science\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IPTEK: The Journal for Technology and Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12962/j20882033.v31i2.6338\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IPTEK: The Journal for Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12962/j20882033.v31i2.6338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
如今科技的发展使人们更容易获取信息。其中之一是查找一个地方的信息。许多潜在的游客会阅读去过一个地方的人的评论,以了解他们对这个地方的评价。对别人的评论的意见是非常有影响力的,影响别人的决定在评估一个地方,他们想要访问。意见分析可以通过对酒店顾客评论进行情感分析来完成。使用的数据是Tripadvisor网站上对东爪哇酒店的旅行者评论。通过在旅游网站上爬行获取游客评论数据,使用TF-IDF方法对评论进行预处理和加权,得到非结构化评论数据。分类过程使用支持向量机方法从旅行者评论中找到正面或负面的意见。根据分类结果,在泗水获得最正面评价的酒店是Harris Hotel Gubeng和Pop!古堡酒店的评论数相同,252条评论。相比之下,在玛琅获得最积极评价的酒店是哈里斯玛琅酒店,有311条评论。意见分析结果有望帮助酒店经理评估和开发,以增加游客访问量。
Opinion Analysis of Traveler Based on Tourism Site Review Using Sentiment Analysis
Technology development nowadays makes it easier for people to access information. One of them is to find information regarding a place. Many prospective visitors would read reviews from people who have visited a place to find out how they rate a place. Opinion on other people’s reviews is very influential in influencing others’ decisions in assessing a place they want to visit. Opinion analysis can be done by conducting a sentiment analysis of hotel customer reviews. The data used are traveler reviews of hotels in East Java on the Tripadvisor site. Traveler reviews data was taken by crawling on tourist sites, and the unstructured reviews data would be a preprocessing and weighted term from reviews using the TF-IDF method. The classification process is done using the support vector machine method to find opinions from traveler reviews, which are positive or negative. Based on the classification results, hotels that have the most positive sentiments in Surabaya are Harris Hotel Gubeng and Pop! Hotel Gubeng with the same number of reviews, 252 reviews. In comparison, hotels with the most positive sentiment in Malang are Harris Hotel Malang with 311 reviews. The opinion analysis results are expected to help the hotel manager evaluate and develop to increase the number of tourist visits.