03028nas a2200517   4500000000100000008004100001260000800042653003600050653002300086653001800109653002000127653002700147653001200174653002300186653002300209653001900232653002800251653002800279653001500307653002000322653002300342653002100365653003200386653002300418653001200441653002000453653002000473653001200493653001800505653001000523653002100533653002300554653001600577653002000593653001700613653002300630653002700653100001500680700001600695700001300711700001400724245012400738490000900862520162500871022001402496       2022                            d  capr10aClassification (of information)10aCultural heritages10aData Analysis10aDigital museums10aDigital reconstruction10amuseums10aSentiment Analysis10aSentiment analysis10aSupport vector10aSupport vector machines10aSupport vectors machine10aTechnology10aUnbalanced data10aUnbalanced support10aUser evaluations10aUser experience evaluations10aUsers  experiences10aVectors10aVirtual reality10aVirtual reality10aarticle10adata analysis10ahuman10ahuman experiment10ainformation center10aInheritance10areference value10aSatisfaction10asentiment analysis10asupport vector machine1 aXiang Chen1 aZhiwei Chen1 aLei Xiao1 aMing Zhou00aA Novel Sentiment Analysis Model of Museum User Experience Evaluation Data Based on Unbalanced Data Analysis Technology0 v20223 aWith the development of virtual reality and digital reconstruction technology, digital museums have been widely promoted in various cities. Digital museums offer new ways to display and disseminate cultural heritage. It allows remote users to autonomously browse displays in a physical museum environment in a digital space. It is also possible to reproduce the lost heritage through digital reconstruction and restoration, so as to digitally present tangible cultural heritage and intangible cultural heritage to the public. However, the user s experience of using digital museums has not been fully and deeply studied at present. In this study, the user s experience evaluation data of digital museum are classified and processed, so as to analyze the user s emotional trend towards the museum. Considering that the user s evaluation data are unbalanced data, this study uses an unbalanced support vector machine (USVM) in the classification of user evaluation data. The main idea of this method is that the boundary of the support vector is continuously shifted to the majority class by repeatedly oversampling some support vectors until the real support vector samples are found. The experimental results show that the classification obtained by the used USVM has a good practical reference value. Based on the classification results of the evaluation data, the construction of the digital museum can be further guided and maintained, thereby improving the user experience satisfaction of the museum. This research will make an important contribution to the construction of the museum and the inheritance of culture.  a1687-5265