Effects of official versus online review ratings

Ghimire, Binam; Shanaev, Savva; Lin, Zhibin

doi:10.1016/j.annals.2021.103247

Cited by 10 publications

(3 citation statements)

References 7 publications

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“…The number of global tourists witnessed exponential growth in the decade before the pandemic arrived. Some of the dominating reasons that fueled the tourism industry belong to technological interventions, such as social media, the proliferation of the Internet, and the mobile revolution that gave “information” power to consumers to search, review, finalize, and book online from the comfort of their homes (Ghimire et al, 2022). Industry and hotels paid great attention to what customers were saying (online feedback) as positive reviews (word‐of‐mouth) became a catalyst to drive future revenues (Nowacki & Kowalczyk‐Anioł, 2022).…”

Section: Resultsmentioning

confidence: 99%

Four decades of sustainable tourism research: Trends and future research directions

Agarwal,

Mehrotra,

Mishra

et al. 2024

Journal of Tourism Research

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With the growth of sustainable tourism research and its practical relevance in today's world, it is important to integrate and synthesize the vast amount ofintellectual work on this topic. This research applies a novel and robust structural topic modeling technique to analyze textual data from a total of 3289 research articles on sustainable tourism published between 1978 and 2022. The topics identified have been classified into macro, meso, and micro levels. Further, we compared and contrasted research themes across three time periods to provide a coherent, cohesive, and holistic overview of the extant literature in each period and discuss their contributions to knowledge. This article presents the publication trends, research evolution in the last four decades, and identifies emerging topics and future research opportunities to advance knowledge.

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Section: Resultsmentioning

confidence: 99%

Four decades of sustainable tourism research: Trends and future research directions

Agarwal,

Mehrotra,

Mishra

et al. 2024

Journal of Tourism Research

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“…The predominance of positive feedback is an incentive for businesses to raise prices for their goods or services to maximise their profits [10]. This prompts unscrupulous businesses to manipulate the customer reviews and ratings with cheating reviews, rigging the feedback scoring, etc.…”

Section: Analysing Medical Service Reviews As a Natural Language Text...mentioning

confidence: 99%

Advancing Semantic Classification: A Comprehensive Examination of Machine Learning Techniques in Analyzing Russian-Language Patient Reviews

Kalabikhina,

Moshkin,

Kolotusha

et al. 2024

Mathematics

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Currently, direct surveys are used less and less to assess satisfaction with the quality of user services. One of the most effective methods to solve this problem is to extract user attitudes from social media texts using natural language text mining. This approach helps to obtain more objective results by increasing the representativeness and independence of the sample of service consumers being studied. The purpose of this article is to improve existing methods and test a method for classifying Russian-language text reviews of patients about the work of medical institutions and doctors, extracted from social media resources. The authors developed a hybrid method for classifying text reviews about the work of medical institutions and tested machine learning methods using various neural network architectures (GRU, LSTM, CNN) to achieve this goal. More than 60,000 reviews posted by patients on the two most popular doctor review sites in Russia were analysed. Main results: (1) the developed classification algorithm is highly efficient—the best result was shown by the GRU-based architecture (val_accuracy = 0.9271); (2) the application of the method of searching for named entities to text messages after their division made it possible to increase the classification efficiency for each of the classifiers based on the use of artificial neural networks. This study has scientific novelty and practical significance in the field of social and demographic research. To improve the quality of classification, in the future, it is planned to expand the semantic division of the review by object of appeal and sentiment and take into account the resulting fragments separately from each other.

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“…The reaction of travelers to different hotel services, facilities, and other amenities and their actual satisfaction from these factors are likely to vary across destination locations, cultures, climates, etc. Thus, it is crucial to establish, review, and revise the measures and the composition of the factors that determine reliable and objective official ratings locally, such as those developed for restaurants in Newcastle, UK [ 24 ] and tour packages in the UK [ 25 ]. Hence, empirical investigations of the relationship between official ratings and customer satisfaction at a particular location are critical to the development and success of the industry in the area.…”

Section: Introductionmentioning

confidence: 99%

Rating vs. Reviews: Does official rating capture what is important to customers?

Arzaghi

Genç

Naik

2023

Heliyon

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Effects of official versus online review ratings

Cited by 10 publications

References 7 publications

Four decades of sustainable tourism research: Trends and future research directions

Four decades of sustainable tourism research: Trends and future research directions

Advancing Semantic Classification: A Comprehensive Examination of Machine Learning Techniques in Analyzing Russian-Language Patient Reviews

Rating vs. Reviews: Does official rating capture what is important to customers?

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