Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 15, No. 2, 2024 309 The Study of Tourist Experience in Historical and Cultural Towns Based on Online Texts: A Case Study of Gongtan Ancient Town Feiyu Zhu, Wenli Wang * School of Management, Chongqing University of Technology, Chongqing 400054, China * Corresponding author: Wenli Wang (Email: zfy15993245265@163.com) Abstract: This paper takes Gongtan Ancient Town of Chongqing as a case study, takes the online comment text of tourists on the websites of Ctrip and Dianping as data, analyzes the online text through content analysis, and uses ROST CM-6 software to conduct word frequency, emotion and semantic network analysis, aiming to deeply explore the tourist experience of Gongtan Ancient Town. The results show that: (1) Tourists' experience of Gongtan Ancient Town consists of five dimensions: tourist destination perception, sensory experience, physical and mental experience, tourist destination characteristic experience and service experience. (2) Natural scenery, local characteristics and service guarantee are the main tourist attractions of Gongtan Ancient Town.(3) Tourists' overall experience and perception of tourism in Gongtan Ancient Town tend to be positive emotions. Tourists' dissatisfaction mainly comes from heavy traffic jams during holidays, poor service attitude of staff and poor accommodation conditions. (4) The semantic network is divided into three levels: the core area is the tourists' objective cognition of the scenic spot name and location; The sub-core circle is the cultural cognition of the ancient town and the characteristic architecture and activity projects; The edge layer is the image characteristic cognition and tourism evaluation of the ancient town. In addition, some optimization suggestions are put forward for the existing problems of Gongtan Ancient Town. The research results not only provide a scientific basis for the tourism development and construction of Gongtan Ancient town, but also provide a reference for the optimization of tourist experience in other ancient towns. Keywords: Web text, Visitor experience, Gongtan ancient town. 1. Introduction With the rapid development and wide popularization of Internet technology, a tourism phenomenon characterized by social interaction and tourist information exchange has appeared. In this process, tourist review has gradually become an important part of tourism research. Modern travelers use online platforms to publish and update travel-related content, share and evaluate their travel experiences. Tourist reviews not only provide rich tourism information for potential tourists, but also provide reference for tourism destination managers to improve services and enhance tourist satisfaction. Online text is the permanent information spontaneously generated and easily obtained by tourists. With the advantages of large sample size and good accessibility, tourists have real and intuitive impression and evaluation of destinations [1], which gradually attracts extensive attention from scholars in the field of tourism research at home and abroad [2]. At present, there are relatively few researches on web text analysis in the field of tourism abroad, and they are mainly concentrated in the past five years. Although some relevant research literature can be found in Emerald and Elsevier databases, the level discussed in these literatures is not extensive, and the research depth is also insufficient. The research mainly focuses on sentiment analysis, tourism demand forecasting and sustainable development. For example, Monsalve-Pulido J et al. proposed a multimodal sentiment analysis model of Spanish tourism data based on the analysis of online texts [3]. Colladon F used social network and semantic analysis methods to analyze online tourism forums and forecast tourism demand based on them [4]. Seok H analyzed the sustainable tourism value of graffiti tourism in Bogota, Colombia through social media [5]. Compared with foreign countries, domestic tourism research based on web text analysis is more and wider in scope, mainly focusing on tourists and tourism destinations. On the one hand, it is the psychological analysis of tourists, such as emotion analysis, tourist perception, tourist satisfaction, and on the other hand, it is the tourism demand prediction and destination attention of tourist destinations. For example, Cheng Cuiqiong made an emotional analysis of online travel notes and obtained the temporal distribution rule of tourists' emotional tendency towards tourist destinations [6]. Qiao Guorong takes the Internet tourism data of immersive tourism performance as the research object and conducts qualitative research on tourists' perception based on embodied theory and "cognitive-emotion" model [7]. Zhao Chunyan took the ancient town of Qingyan in Guizhou Province as an example, took the tourist comment text on Ctrip website as the data source, and used text content analysis to study the influencing factors of tourist satisfaction[8]. Chen Jian took social network data as the entry point, collected travel-related text data, and quantitatively processed the data through the sentiment analysis of BERT model. It effectively solves the problem of insufficient accuracy caused by the limited data sources of the tourism passenger demand forecasting model in the new information environment of the mobile Internet [9]. Song Danke took the historical and cultural district of Yueyang City, Hunan Province as an example, counted the number of visitors' attention to high frequency words in text on the Internet platform, constructed an analysis category of hot topics, and explored the tourists' preference for hot topics [10]. Most of its research data comes from user comments and feedback from online service websites (such as Ctrip and 310 Hornet's Nest), social media platforms (such as Weibo and Douyin), online forums and communities (such as Zhihu and Douban), etc. Most of the research areas are urban scenic spots, traditional villages, natural scenic spots and so on. In addition, as the real evaluation of tourist destinations and the expression of inner emotions, online text is an important data source for tourist experience research. With the advent of the era of experience economy, tourism experience has become the focus of tourism and a hot topic in the academic research field. Foreign scholar Boorstin was first involved in the study of tourism experience [11], and later foreign scholars conducted research on the nature, type, motivation, quality and other aspects of tourism experience [12-14]. Compared with foreign countries, in recent years, domestic tourism experience has produced abundant research results and diversified research methods. Xie Yanjun, a representative scholar, has made great contributions in the field of tourism experience research, mainly focusing on the concept, construction and formation mechanism of experience [15-17]. Most research methods in this field are qualitative analysis. Although some scholars use statistical methods to explore tourist experience in tourist destinations, most of them focus on rural tourism destinations [18] and wetland tourism destinations [19], and few quantitative research results on tourist experience in historical and cultural heritage tourism destinations are seen. Gongtan Ancient Town is a famous historical and cultural town in China and the first historical and cultural town in Chongqing. Through content analysis, ROST CM 6.0 software is used to study the tourist comments on the network platform, and the tourist experience of Gongtan Ancient town is analyzed from three aspects: word frequency, emotion and semantic network, in order to provide reliable reference opinions for the tourism development and optimization of the ancient town. 2. Research design 2.1. Overview of the Research Site Gongtan Ancient Town, located in the west of Youyang Tujia and Miao Autonomous County, Chongqing City, is an ancient town with a history of more than 1700 years and is the bright pearl of Wujiang Gallery. It is not only China's historical and cultural town, the first historical and cultural town in Chongqing, but also the national AAAA level tourist attraction, and the first of the 20 protected historical and cultural towns in Chongqing. As a famous tourist resort in Chongqing, Gongtan Ancient Town has a unique geographical location, located in the junction of three counties, with a long history and rich cultural heritage. With its unique geographical location and rich historical and cultural resources, Gongtan Ancient Town has become a scenic spot integrating natural landscape and folk customs. As a well-preserved and large-scale architectural complex of Ming and Qing Dynasties in China, Gongtan Ancient Town has about three kilometers of SLATE streets, unique firewalls, simple and quiet Siheyuan, stilted houses of different shapes and other historical buildings, providing tourists with a rich sensory experience. At the same time, the folk customs and local characteristics of Gongtan ancient town also create a strong cultural atmosphere for tourists. Most tourists learn the details of the ancient town through the Internet, are deeply attracted and famous, and make real comments on the place after the tour. These comments of tourists have important reference value for tourism research and scenic spot improvement. 2.2. Data Sources Ctrip is the largest comprehensive tourism website in China. It was founded early, has a large number of users, and has a large number of tourist comment data and rich content [20]. Dianping is a comprehensive information and evaluation platform for tourism, providing users with a full range of travel service experience. The platform covers a large number of travel-related content, including tourist attractions, hotels, catering, leisure and entertainment, shopping and other aspects, so that users can obtain all kinds of information needed for tourism in a one-stop shop. The comment section of the two websites contains the user's personal and comment information, including nickname, portrait, rating, IP location, time, comment text, pictures, etc. Among them, the comment content and time is the information included in all user reviews. This paper takes the tourist comments of Gongtan Ancient Town as the research object. By using the text mining method, the Octopus collector web crawler tool was used to climb the tourist comments texts on Ctrip and Dianping websites from 2011.05.01 to 2024.03.01. Among them, 537 comments were obtained from Ctrip and 1597 from Dianping. A total of 2,134 comments on Gongtan Ancient Town were received. A preliminary manual identification and screening was carried out on the 2134 comments collected, and 609 default comments, partial duplication and meaningless comment data were deleted. Finally, 1524 valid comments were obtained, including 530 from Ctrip and 994 from Dianping, with a total of 192,189 words. 2.3. Data processing In this paper, tourists' online comments on Gongtan Ancient Town collected from Ctrip and Dianping websites are taken as research samples, and network text analysis is used to simplify, compress and classify the content of the collected comments, so as to grasp the tourists' attention, emotions and behavior characteristics. In order to improve the accuracy of the research and minimize the impact of data errors on the scientificity and rigor of the research, the following manual browsing process was carried out on the collected texts to screen and sort out the obtained text contents before systematic analysis. (1) Unify traditional Chinese and English into simplified Chinese; (2) Correct typos in the text, (3) Delete advertisements and comments that are all symbols, and delete comments that have nothing to do with Gongtan Ancient Town; (4) Text review. Review the text content to get the final valid comment text, and finally organize it into one TXT text. After processing the text by the above method, the number of words is reduced from 192189 to 191124. ROST CM 6.0 is an important software developed and coded by Professor Shenyang of Wuhan University. It is the only large-scale free social computing platform to assist humanities and social science research in China. This powerful software can perform a series of text analysis tasks such as micro-website analysis, browsing analysis, word frequency statistics, traffic analysis and cluster analysis, providing researchers with comprehensive and in-depth data support. The software is used to import the processed valid 311 texts and make systematic statistics on them, then carry out word frequency analysis, emotion analysis and social semantic network analysis, and classify high-frequency words to obtain tourist experience elements, and finally get the tourist experience results of Gongtan Ancient Town. 3. Data analysis 3.1. Word frequency analysis The evaluation of tourists to the scenic spot can reflect the experience of tourists after the end of the tour in the scenic spot. ROST CM 6.0 software was used to analyze the word frequency of the words representing travel experience in the reviews, and the nonsense words, synonyms and synonyms were excluded. In addition, since adverbs and pronouns had no actual analytical meaning, the high-frequency words retained were nouns, adjectives and verbs. After processing, the top 50 high-frequency words are collected and sorted by word frequency from high too low to obtain the high- frequency words evaluated by Gongtan Ancient Town, as shown in Table 1. The higher the word frequency, the more frequently the word appears in the travel notes, and the higher the tourists' attention. Table 1. High frequency words in online text comments by tourists in Gongtan Ancient Town Nu mbl e Frequently used words Freq uenc y Nu mb le Frequently used words Freq uenc y 1 Ancient town 1896 26 pretty 144 2 Gongtan 1334 27 Commerciali zation 138 3 Wujiang River 1181 28 Travel 122 4 Gallery 531 29 Culture 120 5 View 531 30 Slab stone 118 6 Place 369 31 Tour 116 7 Right 364 32 Hotel 105 8 Scenic spot 327 33 Traffic 101 9 Youyang 282 34 Live 99 10 Admission ticket 279 35 Expediency 98 11 Inn 237 36 Take photos 96 12 Feature 225 37 Breath 91 13 Feel 224 38 Price 85 14 Pleasure boat 222 39 Intersection 83 15 Suit 216 40 Style 83 16 History 210 41 Parking lot 81 17 Stilted building 207 42 Comfy 81 18 Be worth 198 43 Mung bean 79 19 Quiet 191 44 Dark green 77 20 Unit 165 45 Quay 75 21 Recommend ed 162 46 Night scene 74 22 By boat 159 47 Be pleased 74 23 Be fond of 155 48 Gourmet 71 24 Small town 152 49 Beautiful view 70 25 Put up 150 50 Cheap 69 According to the word frequency statistics table and evaluation text, high-frequency words are classified and statistically analyzed, which mainly includes five categories: tourist destination perception, tourist sensory experience, tourist physical and mental experience, tourist destination characteristic experience and tourist destination service experience (see Table 2). Table 2. Classification analysis of the top 50 high-frequency words Sort High frequency words and their word frequencies Tourist destination perception Ancient Town (1896), Gongtan (1334), Wujiang (1181), Scenery (531), Gallery (451), Scenic spot (327), Youyang (282), History (210), Town (152), Culture (120), Intersection (83) Tourist sensory experience Beautiful (144), Ssightseeing (116), Atmosphere (91), night view (74), beauty (70), food (71) Tourist physical and mental experience Nice (364), Feel (224), Fit (216), Worth (198), Quiet (195), Recommend (162), Like (155), Commercial (138),Travel (122), Live (99), Convenient (98), Take Photos (96), Comfortable (81), Cozy (74) Tourist destination characteristic experience Place (369), Feature (225), Cruise (222), Stilted House (207), Architecture (165), Boat (159), Slate (118), Style (83), Mung bean (79), Pier (75) Tourist destination service experience Tickets (279), Inns (237), Accommodation (150), Advice (122), Hotel (105), Transportation (101), Price (85), Parking (81), Cheap (69) As can be seen from Table 2, tourists' perception of the tourist destination of Gongtan Ancient Town mainly includes "ancient town", "scenery", "history" and "culture". Tourists are very interested in the history, culture and natural scenery of Gongtan Ancient Town. The sensory experience of tourists is mainly reflected in "beautiful", "sightseeing", "beautiful scenery" and "delicious food". The sight, smell and taste of tourists are satisfied during the tour, and the beautiful food is welcomed by tourists. Visitors experience of body and mind embodied in the "good" "worth" "quiet" "recommend" "like", "convenient" "pictures" "comfortable" "sweet". It can be seen that tourists are very satisfied with the physical and mental experience of Gongtan Ancient Town, relaxed during the journey, and are willing to recommend Gongtan Ancient Town to others. Among them, there is the word "commercialization", and more comments are that tourists feel that the commercialization of Gongtan Ancient town is not high, and it belongs to the original ecological town. The characteristic experience of tourists to Gongtan Ancient Town mainly includes "cruise ship", "stilted building", "architecture", "SLATE", "style", "mung bean" and "dock". Visitors to the ancient town of Gongtan saw the local architecture and tried the boat program. In terms of tourist destination service experience, the most popular comments from tourists are scenic services and facilities such as tickets, accommodation, transportation and prices. Most tourists find the various services in Gongtan Ancient Town cheap. In general, tourists enjoy and are satisfied with the travel experience of Gongtan Ancient Town. Natural scenery, local characteristics and service guarantee are the main advantages and characteristics of Gongtan Ancient Town to attract tourists. 312 3.2. Sentiment Analysis The positive emotional response of tourists often represents higher satisfaction. The emotion analysis of content analysis is mainly to quantitatively score and evaluate the expression of emotion involved in the text information of tourists' comments, so as to deeply analyze the emotional state of tourists. This method can help us to understand the psychological feelings of tourists more accurately and provide strong data support for tourism research. ROST CM 6.0 software was used to conduct emotion analysis on tourists' comments, and an emotion analysis table was obtained (see Table 3). The results showed that in tourists' perception of tourism experience in Gongtan Ancient Town, positive emotions accounted for about 76.12%, neutral emotions were less, and negative emotions accounted for about 23.55%. Some tourists were not satisfied. The satisfaction of tourists to Gongtan Ancient Town is relatively high, and the experience perception is more positive. According to the real feedback of tourists' comments, Gongtan Ancient Town is a famous historical and cultural town in China, the starting point of Youyang's "Qianli Wujiang, hundred-mile Gallery", and a tourist scenic spot integrating natural landscape and folk customs. Visitors can not only experience the natural scenery of the ancient town, but also taste the humanistic charm of Gong Tan. The dissatisfaction of tourists is concentrated in the following aspects: (1) More people on holidays and traffic jams. Tourist comments: "New Year's Day traffic jam, from Chongqing to Gongtan almost 6 hours" "National Day to play, people really a little too much, the road is also a little traffic jam" "National Day to go, a lot of people a little traffic jam"; (2) The service attitude of the staff is poor. Comments from tourists: "Especially when buying stamps at the post office, the attitude is very bad", "especially the two men who registered at the gate of the cruise ship, the attitude is very bad", "the service attitude is very bad, the sightseeing shuttle bus even openly drove the queue of passengers to get off"; (3) Poor accommodation conditions. Tourist comments: "Because they are stilted buildings, the sound insulation is not very good" "The place to live is also very angry, the room is two beds are full, basically no extra space" "The room ground is dirty, some bedding is moldy". It is because of these deficiencies that some tourists experience less than expected, reducing the tourism satisfaction of Gongtan Ancient town. At the same time, this also shows that there are problems in the diversion, reception and security of staff in the scenic spot, which affects the tourist experience. Table 3. Emotion analysis table of tourists' comments in Gongtan Ancient Town Affective category Ratio (%) Frequency (times) Intensity Ratio (%) Frequency (times) Positive emotion 76.12 1160 General (5,15) 16.73 255 Moderate (15,25) 17.72 270 Height (25,+∞) 41.67 635 Neutral emotion 0.33 5 0.33 5 Negative emotion 23.55 359 General [-15,5) 14.13 215 Moderate [-25,-15] 4.71 72 Height (-∞,-25) 4.71 72 Total 100 1524 100 1524 3.3. Semantic Network Analysis ROST CM 6.0 software is used to conduct in-depth semantic network analysis on the content of visitors' comments, and an intuitive semantic network diagram is drawn accordingly (see Figure 1). In the semantic network diagram, the closer a node is to the central node, the closer the relationship between the node and the central node is. The semantic network analysis diagram of tourist experience in Gongtan Ancient Town is distributed in a divergent way, showing a three-layer structure. The first layer is the core area, which is the tourists' objective cognition of the name and location of the scenic spot. The smallest circle is formed by the highest common words such as "ancient town", "Gongtan", "Wujiang" and "gallery", among which the word "ancient town" is located in the most central position. The second floor is the secondary core circle, which is the description of the cultural cognition, characteristic buildings and activities of Gongtan Ancient Town, and also the further understanding of the first floor. It is composed of "history", "culture", "place", "scenery", "architecture", "stilted buildings", "tickets", "scenic spots", "cruise ships" and "accommodation". As can be seen from Figure 2, in the second layer, "history" and "culture", "place" and "scenery", "ticket" and "scenic spot" maintain a strong correlation. The third layer is the edge layer, which reflects the tourists' cognition of the image characteristics and tourism evaluation perception of Gongtan Ancient Town, and is a further description and supplement of the core circle and sub-core circle. It is mainly composed of words such as "quiet", "beautiful", "night view", "comfortable", "feature", "photo", "experience", "worth" and "traffic". 313 Figure 1. The semantic network diagram of tourist experience in Gongtan Ancient Town According to the analysis, tourists' overall cognition of Gongtan Ancient Town is mainly based on regional location and local characteristics. The natural landscape, local architecture and activities, such as "scenery", "stilted buildings" and "cruise ship", are the most profound and attractive factors for tourists' experience. 4. Conclusion and Suggestion 4.1. Conclusion Through the analysis of tourists' online evaluation data of Gongtan Ancient Town, the following conclusions can be drawn: In terms of tourist experience, it can be divided into five categories: tourist destination perception, tourist sensory experience, tourist physical and mental experience, tourist destination characteristic experience and tourist destination service experience. First of all, through the word frequency statistical analysis of the text data of tourists' comments, the three core high- frequency words are: "ancient town", "Gongtan" and "Wujiang". Secondly, the overall emotion of tourists towards Gongtan Ancient Town tends to be positive, and the overall satisfaction and recommendation intention are relatively strong. Less neutral emotion; the negative emotions are mainly concentrated in the holiday traffic jams, staff service attitude is poor, poor accommodation conditions and so on. Finally, the semantic network analysis of the data shows that "Ancient town" is in the core position, while "Gong Tan" and "Wujiang" are also in the core position. These three are the core areas, which are the tourists' objective cognition of the name and location of the scenic spot. Tourists' cultural cognition and characteristic buildings and activity projects of Gongtan Ancient Town are in the secondary core circle, and then the edge layer is the tourists' cognition and tourism evaluation of the image characteristics of Gongtan Ancient Town. Step by step, the overall show the tourists to the Gongtan ancient town from the inside out gradually in-depth understanding. 4.2. Conclusion According to the results of text analysis and combined with the actual situation, this paper puts forward five tourist experience improvement strategies. (1) Enhance local characteristic experience and enrich landscape and cultural connotation Gongtan Ancient town is located in Youyang with profound cultural deposits and has unique geographical advantages. While optimizing the existing projects, the scenic spot can actively develop regional cultural activities such as dock culture, food culture and folk culture, improve the interest and interaction, and organically connect the activities in order to enrich the tour experience and improve the satisfaction of tourists. (2) Improve service experience and standardize operation and management Enrich the feedback path, so that the problems reflected by tourists can be effectively solved. Strengthen the local operation and management, improve the accommodation conditions, increase the type and quantity of catering in the ancient town as appropriate, and meet the public demand for quality and quantity. In addition, the problem of parking in scenic spots needs to be solved urgently. Gongtan Ancient Town scenic spot can build parking lots in appropriate areas, add more parking Spaces, suggest to increase accessible public transport, guide tourists to choose public transport travel, and improve the efficiency of public transport operation to meet the different travel needs of tourists. (3) Strengthen the digital management of peak passenger flow Peak tourist flow and scenic area management are important factors affecting tourists' perception and experience. However, weather prediction, monitoring and management, and popular science knowledge are not mentioned in the text, which indicates that the digital application of Gongtan Ancient Town is not deep enough. We should increase the development of digital technology, add special science popularization system, improve the forecasting and management ability of scenic spots, and scientifically control 314 the passenger flow. In addition, in view of the long queuing time of tourists in Gongtan Ancient Town, theme park managers can start from optimizing the booking and purchase system, such as online ticket purchase platforms (such as official websites, public accounts) and offline ticket purchase channels (such as ticket Windows, self-service ticket vending machines) to set time limits on visits and the number of visitors, and reasonably distribute personnel. Gongtan Ancient Town can also through the booking time to the first half hour SMS reminder, on-site booking is expected to queue time reminder, etc., to help tourists reasonably plan their own play schedule, reduce the inevitable queuing. (4) Increase publicity and marketing efforts, and actively use new media The scenic spot can take the new media platform as an important publicity medium and create official accounts, such as the official website, wechat public account, Tiktok account, etc., to do a good job in content output, show the best image of Gongtan Ancient Town, and enhance the attraction and influence of the scenic spot through real-time interaction through live broadcast activities during the festival. At the same time, the scope of cooperation with travel agencies can be expanded to enhance the visibility and reputation of the scenic spot. 5. Credit Authorship Contribution Statement Feiyu Zhu: supervision, writing-review & editing, methodology. Wenli Wang: data curation, supervision, writing-original draft, writing-review & editing, visualization. 6. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 7. Data Availability The authors do not have permission to share data. Acknowledgments This research was funded by Achievements of Chongqing University of Technology's high-quality development Action Plan for Postgraduate Education (Grant No.gzlcx20243421) References [1] L. Chen, L.W. Zhou: A study on the countermeasures to improve the quality of tourist experience from the perspective of Embodiment -- A case study of 918 History Museum, Frontier Economy and Culture, vol. 01 (2024), No.3, p.63- 67.(In Chinese) [2] Y. Gao, J.L. Zhang: A study on tourist perception of Chongqing Garden Expo landscape image based on network data. 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