Online Travel Reviews Research Articles

Tourist attraction reviews based on deep learning Sentiment Analysis System

In recent years, with the rapid development of information technology, online travel reviews have become a key source of information for tourists to understand destinations. In the face of massive and unstructured travel review data, this paper innovatively proposes a sentiment analysis system for tourist attraction reviews based on deep learning. The system cleverly uses the BERT pre-trained model, and combines Bi-LSTM and attention mechanism to significantly improve the accuracy of sentiment classification. In order to verify its effectiveness, this paper conducts experiments on the evaluation data of scenic spots in Hubei Province. The experimental results are very impressive through multi-dimensional indicators such as accuracy, precision, recall, and F1-score. The accuracy rate is as high as 93.5%, the accuracy rate is 94.1% for positive reviews, the accuracy rate for negative reviews is 92.8%, the recall rate is 92.1%, and the F1-score is 92.8%. This fully shows that the system can accurately identify the emotional tendency of tourist attraction reviews, provide a strong basis for scenic spot management, help it adjust service strategies in a timely manner, and also assist tourists to make more informed decisions, providing a reliable technical reference for the digital transformation and intelligent management of the tourism industry.

Exploring Guilin's Destination Image Via User-Generated Content: A Computational Methods

This study quantify mainland China's destination image through international tourists' user-generated content (UGC), with a specific focus on Guilin, utilizing advanced computational techniques such as Latent Dirichlet Allocation (LDA) for topic modeling and sentiment analysis. It systematically evaluates online travel reviews to distill key themes and emotional sentiments that shape Guilin's image, uncovering a rich tapestry of cognitive perceptions and affective reactions related to its natural scenery, cultural engagements, service standards, and logistical facets. The application of topic modeling and sentiment analysis provides a nuanced understanding of the cognitive and affective dimensions defining Guilin's destination image. While positive sentiments largely highlight the region's aesthetic and experiential allure, negative sentiments reveal critical areas for improvement, such as perceived value and infrastructure, which are vital for enhancing tourist satisfaction and reinforcing Guilin's appeal in the global tourism market. This research applies LDA and sentiment analysis to interpret UGC offer a calculable methodological approach for broader application in destination image studies. By aligning perceptual and emotional insights with destination marketing strategies, the findings offer actionable intelligence to optimize tourist experiences and enhance destination loyalty. This approach not only enriches the academic understanding of destination images but also provides practical frameworks for destination managers to harness the full potential of UGC in shaping and refining the global image of tourism locales.

A deep learning method utilizing Bi-GRU for the determination of novelty seeking in online travel reviews

A deep learning method utilizing Bi-GRU for the determination of novelty seeking in online travel reviews

Destination Image Semiotics: Evidence from Asian and European Upscale Hospitality Services

Given the importance of semiotics and destination image (TDI) in the field of tourism and hospitality marketing, this study proposes a conceptual model that integrates Peirce’s semiotic triad, Grönroos’s quality service model, and Morris’s semiotic trichotomies in the TDI formation circle. The new framework aims to measure the contribution of quality hospitality services to online TDI formation. Using scaled comparisons of homogeneous big data, this framework was empirically tested with all two- and three-star Michelin restaurants and a sample of 100 four- and five-star hotels, all located in Asia and Europe, reviewed in 317,979 online travel reviews (OTRs) hosted on TripAdvisor. The results showed that three-star restaurants and five-star hotels are more popular in terms of the number of OTRs, but diners and guests are more satisfied with and loyal to two-star restaurants and four-star hotels. This big data finding contradicts previous survey-based research on quality services. Instead, the results confirm that consumer satisfaction positively affects consumer loyalty. The new approach to the TDI from a semiotic perspective—destination image semiotics—can represent a paradigm shift in the analysis of TDI through user-generated content (UGC). The proposed conceptual framework integrates several sound theoretical models to extract maximum insights from UGC.

Benchmarking Travelling Reviews using Opinion Mining

Online travel reviews offer valuable data, yet it remains uncertain if those most influenced by these reviews actually read them. This research aims to uncover consistent patterns and explain variations in online travel ratings, comments, and reviews. To accomplish this, millions of reviews were collected from Pakistan's top online travel companies, Uber and Careem. Utilizing semantic affiliation analysis, subject terms were extracted, forming a semantic affiliation structure. The findings highlight significant differences among channels concerning topical vocabulary, subject distribution, structural traits, and community links. The network visualization results are particularly noteworthy, as they illustrate connections between key concepts and words within each topic, making them easily understandable. With the proposed logical method, we can better understand the strategic snafus in the travel sector and gain fresh insights into how to dig up popular assessments to better serve tourists, lodging establishments, and trade groups.

Information processing of travel barrage reviews: effects of social presence and opinion leaders on the relationship between barrage reviews and travel intention

ABSTRACT Barrage as an emerging type of user-generated review has been adopted by almost all tourism live-streaming platforms. However, few studies have been conducted to understand how travel barrage review attributes affect travel intention (TI). This study adopts a mixed method to examine the effectiveness of the content and form attributes of travel barrage reviews in influencing potential tourists’ travel intentions. Two studies jointly revealed that potential tourists were more willing to adopt the central path to process barrage content, while perceived trust and usefulness played mediating roles. Conversely, potential tourists were more willing to adopt the peripheral path to process barrage form when social presence played a mediating role. Furthermore, the moderating effect of opinion leaders on the relationship between barrage reviews and changing TI was considered. This study extended previous work in the online travel reviews field and provided guidance to tourism practitioners on how to engage in live-streaming marketing.

Attributes influencing guests’ experiences: a comparison of nonprofit and for-profit peer-to-peer accommodation platforms

Peer-to-peer accommodation has generated an ecosystem of platforms with different business models (i.e., for-profit and nonprofit). This study aims to identify and compare attributes that influence guests’ experiences as reviewed on the for-profit platform Airbnb and the nonprofit platforms Couchsurfing.com and HomeExchange.com according to a three-dimensional experience theoretical model and a methodological approach to interpret these attributes. The study used text-mining techniques to analyze 772,768 online travel reviews representing Spain’s four most-visited cities. Findings show that attributes influencing guests’ experiences in the case of nonprofit platforms relate to the authenticity dimension of experience (e.g., existential values and travel philosophy). Furthermore, guests reported that their guest–host interaction was the most representative attribute and that, unlike with Airbnb, such interaction helped to create a more authentic experience. By contrast, attributes of guests’ experiences in the case of for-profit platforms related to the physical amenities and characteristics that guests would expect to find in hotels. Those results can allow destination managers and accommodation practitioners to better understand users of peer-to-peer accommodations and thereby design more suitable strategies and experiences for them.

Hospitality Discourse on Social Media: Evaluating Online Complaints and Service Recovery for Luxury Hotels

The number of hotel visitors who post their personal experiences on online hotel review forums after their trips has increased significantly in the digital age. However, there is limited linguistic research that examines 1) how international travelers communicate online to share their negative hotel experiences and 2) how luxury hotel management resolves complaints and regains customer trust. This study examines electronic word-of mouth (eWOM) in the reviews and focuses on posted by international travelers who stayed at Hong Kong's 5-star luxury hotels and e-replies posted by hotel management groups. The data are based on authentic reviews collected from an online travel review forum. The present study employs appraisal analysis (Martin & White, 2005) and specifically the engagement system to investigate heteroglossic voice in 38 sets of complex e-complaints and responses totaling 17,344 words. The findings contribute to the advancement of professional discourse in hospitality service encounters.

Dynamics in accommodation feature preferences: exploring the use of time series analysis of online reviews for decomposing temporal effects

PurposeThis study aims to explore the use of time series analyses to examine changes in travelers’ preferences in accommodation features by disentangling seasonal, trend and the COVID-19 pandemic’s once-off disruptive effects.Design/methodology/approachLongitudinal data are retrieved by online traveler reviews (n = 519,200) from the Canary Islands, Spain, over a period of seven years (2015 to 2022). A time series analysis decomposes the seasonal, trend and disruptive effects of six prominent accommodation features (view, terrace, pool, shop, location and room).FindingsSingle accommodation features reveal different seasonal patterns. Trend analyses indicate long-term trend effects and short-term disruption effects caused by Covid-19. In contrast, no long-term effect of the pandemic was found.Practical implicationsThe findings stress the need to address seasonality at the single accommodation feature level. Beyond targeting specific features at different guest groups, new approaches could allow dynamic price optimization. Real-time insight can be used for the targeted marketing of platform providers and accommodation owners.Originality/valueA novel application of a time series perspective reveals trends and seasonal changes in travelers’ accommodation feature preferences. The findings help better address travelers’ needs in P2P offerings.

How eco-service quality affects tourist engagement behaviour in ecotourism: eco-consciousness and eco activity-based learning and S-O-R Theory

ABSTRACT This study aims to examine the growing role of eco-consciousness and eco-activity-based learning in the eco-service quality model and their effect on tourist engagement behaviour in ecotourism destinations. Based on the regression and FsQCA analysis on online travel reviews, the result shows a significant impact of eco-service quality on tourist satisfaction, further leading to their engagement behaviour in revisit, recommendation, and learning engagement. Interestingly, the result reveals that tourists’ eco-consciousness significantly stimulates their revisit engagement in ecotourism destinations. Furthermore, eco-activity-based learning also significantly moderates the relationship between the eco-tangible dimension (physical facilities provided in the ecolodges or hotels that are safe and sound for the environment) and tourists’ satisfaction. Theoretically, this study adds value to ecotourism literature by extending tourist engagement from psychological (satisfaction) to behavioural engagement (revisit, recommendation, learning engagement). Furthermore, using the S-O-R theory, this study highlights the stimuli of tourist satisfaction and subsequent behavioural responses through tourist engagement behaviour in the ecotourism context.

Online travel reviews and tourist trust: a SOR perspective

Purpose This study aims to examine the impact of online travel reviews (OTR) on tourists’ intention to travel based on the stimulus–organism–response (SOR) model. Further, it explored the mediating effects of tourist trust in OTR. Design/methodology/approach In this direction, this study proposes and empirically validates a conceptual model after collecting data from 299 Indian consumers. Proposed hypotheses were tested by applying the structural equation modelling technique. Bootstrapping method was used for mediation testing. Findings The findings revealed that various attributes of OTR exert differential impacts on travel intention. The study also confirmed the mediating role of tourist trust in OTR. Practical implications This study offers significant practical implications for travel marketers. To capitalize on OTR, travel marketers are recommended to develop an effective and efficient online reviews management system. This will improve the quality, valence, quantity and consistency of OTR, which in turn will enhance tourist trust in OTR, leading to improved travel intention. Originality/value No empirical evidence has been traced on how OTR enhances tourist trust in OTR and their travel intention. In support of this, the present study proposes and empirically validates an extensive model to comprehend the role of various drivers of OTR in improving tourist trust in OTR, leading to enhanced travel intention based on the SOR model.

Placing African American museums in the American tourism landscape

According to the Association of African American Museums (AAAM), there are more than 200 African American history and cultural museums—or other sites with substantial African American collections such as libraries and archives—across the U.S. Many of these museums had their start shortly after the height of the Civil Rights Movement, with a surge in establishments in the 1970s. Black museums serve to decenter White stories of America and refocus on Black experiences. While geographers have studied an array of memory, heritage, and tourism sites, museums remain understudied and under-theorized. Building upon the subfields of Museum geographies—particularly by considering the concept of museums as theatres of pain—and Black geographies, our research examines the ways these museums are integral to the relationships between Black placemaking and the tourism landscape, which remains steeped in anti-Black racism. Using museum exhibit documentation, semi-structured interviews of museum staff, and content analysis of online travel reviews (primarily TripAdvisor and Google Reviews), this paper analyzes two case studies: The National Afro-American Museum and Cultural Center in Wilberforce, Ohio, and The Colored Girls Museum in Philadelphia, Pennsylvania. Through our two case studies, we show how Black museums enact curatorial practices of commemorative geographies and create redemptive spaces that cultivate not only a homeplace for visitors, particularly for Black Americans and people of the African diaspora but also serve as sites of belonging and joy.

Cooking Classes as Destination Image Contribution: A Serious Leisure Perspective

Gastronomy tourism is of great interest to scholars due to its valuable contribution to destination images. Most studies use quantitative methodology, although mixed-method research provides more valuable insights. This study proposes two complementary theoretical models based on the online gastronomic image and a mixed methodological framework to measure the impact of serious leisure gastronomic activities on the destination image, through the participants’ satisfaction and loyalty. The proposed models are applied to all online travel reviews in English (N = 4536) about cooking classes in two regions –Taiwan and Catalonia– of similar area and political system but different gastronomic cultures. The quantitative analysis shows that the cooking classes in both regions are highly appreciated. Qualitative findings indicate that the price of this serious leisure activity is affordable and show that participants reap social rewards through positive social interactions and personal rewards from three facets: activity settings, instructor attributes, and participant learning.

Promoting Food Tourism Through Digital Media With Special Reference To Sri Lanka As A Tourist Destination

Many travellers recognize food experiences as a must-do activity at travel destinations as much as the interest shown by them, Destination Management Organizations around the world have identified food as a part of special interest tourism and an experience that helps differentiate a destination’s offerings against competitors. The current study set out to explore whether travellers perceive food as a travel attraction that motivates them to travel to a destination and whether food can provide a memorable experience to such travellers and how well destination management organizations promote food tourism through digital media in a setting where many travellers search for information online. The study included a preliminary study in which the opinions of travellers were identified through a content analysis of experiences shared on online travel review sites and social media. Thestudy conducted a qualitative research approach where interviews were conducted to gain further insights into travellers’ food experiences. Further, the effectiveness of promoting food tourism through digital media by destination management organizations was analyzed through a content analysis of textual and visual content on websites. The findings of the study indicate that travellers consider food as a major motive to travel, as an experience booster, a novel and exciting experience, an experience beyond just eating, an aid to learning about locals’ lifestyle, an experience worth recreating and an experience that results in a change in lifestyle becoming a peak touristic experience. It was apparent that Local Destination Management Organizations do not effectively communicate these factors about food experiences through their digital platforms. This study is significant in a theoretical aspect as it presents seven characteristics of food experiences concerning the conceptual model of tourist experience and for applying this model to the digital context taking the destination management organization’s point of view. It is also significant in a practical aspect as it shows the potential of food to be a main attraction for Sri Lanka Tourism and portrays space for improvement in marketing such experiences,especially in digital media.

Analyzing online reviews of foreign tourists to destination attractions in China: a novel text mining approach

ABSTRACT In recent years, China has been gradually improving its tourism services along with its economic development. Inbound tourism not only boosts the economy of China, but also creates issues and challenges for tourism administration. The purpose of this study is to develop a novel text mining approach that combines topic modeling and sentiment analysis for exploring the dynamic evolution of topic intensity of destination attractions and discovering the reasons for foreign tourists’ dissatisfactions. To this end, we propose an LDA-based topic evolution model, develop a tourism-oriented VADER dictionary and introduce an integration method for screening negative reviews. Then, the approach was used to analyze 80,546 online travel reviews from foreign tourists on TripAdvisor for 10 popular destination attractions in China from 2011 to 2019. The findings can help tourism practitioners better understand the changes and trends of the topics over time as well as develop strategies with respect to tourists’ dissatisfactions.

How Online Travel Reviews Sources Affect Travelers’ Behavioral Intentions? Analysis with Source Credibility Theory

ABSTRACT This study used Source Credibility Theory (SCT) to examine the effect of the source credibility factors (SCFs) of travelers’ electronic word of mouth (eWOM) and their adoption on tourists’ hotel booking and review sharing intention. This study used Structure Equation Modeling (SEM) and artificial neural network (ANN) approaches to validate the effect of SCFs on tourists’ behavioral intentions. The study highlighted that all three source credibility factors, such as perceived sender trust, website trust, and organizational reputation, affected functional aspects like eWOM credibility and adoption. The study finds the dual-mediating effect of eWOM credibility and adoption between source credibility factors and eWOM outcomes. This study makes a unique attempt to analyze the roles of various aspects of SCT on tourists’ eWOM behavior. This study contributes to online trust literature by examining the effect of different online credibility factors (surface credibility, presumed credibility, reputed credibility) on online tourist behavior.

How do online travel reviews facilitate informed purchase decisions?

ABSTRACT We analysed the attributes of online travel reviews that facilitate online travel purchasing decisions. In Study 1, we developed and validated a scale for measuring the perceived value of online travel reviews (PVOTR). The PVOTR scale has six dimentions and was based on a literature review and Fuzzy Delphi Method. It was validated with data from 69 undergraduate students and 485 travelers in Taiwan. In Study 2, we examined the impact of PVOTR on the online travel purchasing attitudes of another 469 travelers in Taiwan. PVOTR significantly affected online travel purchasing attitudes through the mediation of reduced perceived complexity.

Sentiment of Chinese Tourists towards Malaysia Cultural Heritage Based on Online Travel Reviews

Analyzing the perception differences and influencing factors of cross-cultural groups in heritage tourism can help heritage sites to formulate differentiated service and improve tourist satisfaction. This research adopted the BERT model to undertake sentiment analysis of 17,555 Chinese online reviews for nine scenic spots in Melaka. Using vocabulary filtering, co-occurrence analysis, and semantic clustering technology, the emotional characteristics of Chinese outbound tourists when they visited heritage sites in Melaka were analyzed, which revealed the factors influencing their positive and negative emotions. Results showed that: 1. The BERT-based deep learning approach can obtain improved sentiment predictive performance. 2. Chinese tourists’ general emotional perceptions of Melaka were positive and they were very interested in heritage sites. 3. The most important reason for the negative emotions of Chinese tourists was a lack of cultural experience in Melaka. This research expands the application of deep learning in the field of tourism, and it helps heritage tourism destinations to improve their marketing plans for Chinese tourists and achieve long-term sustainable development of the destination.

Reconstructing the microbrewery taproom experiencescape through narratives in online travel reviews: A case from Houston, Texas USA

The number of craft breweries on the American landscape has grown exponentially over the past several decades. The literature on craft beer and beer tourism has grown accordingly. Yet, visitors’ experience of the craft brewery taproom remains an under-examined aspect of this literature. O’Dell (2005 ) proposed the idea of examining the landscapes of experiences, or experiencescapes, including the physical and social spaces that allow for the co-creation of experiences. The concept has increasingly been used to examine culinary, gastronomic, and wine tourism experiences. Thus, this exploratory study begins to address the gap in the craft beer and beer tourism literature by reconstructing the experiencescape of craft brewery taprooms from visitor narratives in online travel reviews for microbreweries and taproom breweries in Houston, Texas (USA). The study employs thematic narrative analysis to identify the components of the physical and social environments of the brewery taproom that comprise the experiencescape and contribute to positive, memorable experiences. Findings indicate that consuming the craft beer product is only one part of the taproom experiencescape; breweries must consider the taproom experience holistically. Opportunities exist to facilitate a more conscious experiencescape design to engage visitors’ senses for more immersive and memorable experiences.

Investigating the credibility of online travel reviews adoption in trip planning intention among Indian travellers

Travelers evaluate online travel reviews usage through their argument quality and credibility of the source. As a result, travel marketers such as hoteliers, destination marketers and travel agency websites managers should set up mechanisms to assess tourists' concern to avoid unfavorable experience from social media reviews. Accordingly, this study aims to develop a scale and validate the modified Information Adoption Model (IAM) in the tourism context, while studying the impact of online review usefulness on its adoption. Secondly, the mediation role of travelers' attitude toward online reviews between review usefulness and its adoption is determined. Further, the credibility of online travel review adoption on the behavioral intentions of travelers has been assessed. This paper adapts the modified IAM given by Abedi et al. (2019) to develop scale and provide a comprehensive model in the tourism context. The study used 284 travelers who use online travel reviews from social media for their trip planning to evaluate the proposed model through SmartPLS software. The results show that online travel review usefulness significantly affects online travel review adoption. Secondly, the relationship between online review usefulness and its adoption is fully mediated by the mediating variable (attitude towards online travel reviews). Hence, this empirical paper intends to add to the research on online travel review adoption by travelers for their trip planning, considering the forwarding of information as one of the behavioral intentions along with purchase intentions, which depicts the novelty of this paper.