Research On Influencing Factors Of User Satisfaction In Online Short-term Rental Market

With the emergence of new media such as various e-commerce platforms,and the emergence of shared culture,online short-term rental platforms such as Piggy Short-Term Rental,Airbnb,Tujia.com have become an important choice for short-term accommodation for travelers.Online short-term rental user satisfaction is a basic requirement for forming a good word-of-mouth effect,attracting users,and continuing development of the online short-term rental market.Most consumers have the habit of referring to the online word-of-mouth reputation of the goods or services to be purchased.The main manifestation of Internet wordof-mouth is online reviews,which mainly reflect the real experience of historical users.This article uses empirical research methods such as the selection of important features of online information and the text mining of user online reviews,in order to find the main factors that affect user satisfaction,provide effective and objective theoretical reference for the long-term development of online short-term rental companies,and help landlords and While seizing development opportunities,enterprises attract more potential users in fierce competition and have certain reference significance for potential users and relevant management departments.This article mainly analyzes according to the following process:1)First,the online data set of the online short-term rental platform is obtained through a dynamic web crawler,which is mainly a review text data set,thereby forming a rich industry analysis corpus;2)Then,using The LDA topic model extracts and summarizes topics,and constructs a structural framework of influencing factors for user satisfaction;3)Finally,based on the characteristics of the random forest,the important variables of online information data are extracted,and the sentiment of user satisfaction is obtained through sentiment analysis information,and then use the semantic network to mine co-occurrence high-frequency words in positive and negative emotional corpora.Finally,use the Word2Vec model to calculate the cosine value of emotional polar words,and integrate the positive and negative factors that affect the user experience.The final conclusions can be roughly summarized into the factors related to the landlord,the overall situation of the house,the price,the convenience of the surrounding business districts,and the security of the accommodation.