scholarly journals Topic Modeling of Online Accommodation Reviews via Latent Dirichlet Allocation

2020 ◽  
Vol 12 (5) ◽  
pp. 1821 ◽  
Author(s):  
Ian Sutherland ◽  
Youngseok Sim ◽  
Seul Ki Lee ◽  
Jaemun Byun ◽  
Kiattipoom Kiatkawsin
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Bayesian Hierarchical ◽  
Extant Literature ◽  
Guest Satisfaction ◽  
Hierarchical Statistical Model ◽  
Different Characteristics ◽  
Dirichlet Allocation

There is a lot of attention given to the determinants of guest satisfaction and consumer behavior in the tourism literature. While much extant literature uses a deductive approach for identifying guest satisfaction dimensions, we apply an inductive approach by utilizing large unstructured text data of 104,161 online reviews of Korean accommodation customers to frame which topics of interest guests find important. Using latent Dirichlet allocation, a generative, Bayesian, hierarchical statistical model, we extract and validate topics of interest in the dataset. The results corroborate extant literature in that dimensions, such as location and service quality, are important. However, we extend existing dimensions of importance by more precisely distinguishing aspects of location and service quality. Furthermore, by comparing the characteristics of the accommodations in terms of metropolitan versus rural and the type of accommodation, we reveal differences in topics of importance between different characteristics of the accommodations. Specifically, we find a higher importance for points of competition and points of uniqueness among the accommodation characteristics. This has implications for how managers can improve customer satisfaction and how researchers can more precisely measure customer satisfaction in the hospitality industry.

Measuring Satisfaction and Loyalty of Guests Based on Vietnamese Hotel Online Reviews

2021 ◽  
Vol 11 (2) ◽  
pp. 1-17
Author(s):  
Ha Nguyen Thi Thu ◽  
Tuan Tran Minh ◽  
Tu Nguyen Thi Ngoc ◽  
Binh Giang Nguyen ◽  
Linh Nguyen Ngoc
Keyword(s):  
Data Analysis ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Online Reviews ◽  
Actual Data ◽  
Sentiment Lexicon ◽  
Guest Satisfaction ◽  
Improve Service Quality ◽  
Guest Loyalty

Measuring customer satisfaction is a key task for hotels today. Analyzing online reviews of experienced guests will help the managers to know if guests are satisfied or dissatisfied with the service that they provided. Hence, they have solutions to improve service quality. This study presents a method to measure guest satisfaction based on sentiment lexicon that is developed for hospitality domain to increase the accuracy of the analysis results. Actual data is downloaded from TripAdvisor with 35 four-star to five-star hotels of five cities in Vietnam to analyze guest satisfaction that shows that nearly 80% of customers are satisfied with the quality of Vietnamese hotels. Based on data analysis, the study also evaluating guest loyalty through phrases like “came here several,” “come back,” “recommend,” etc. This rate corresponds to the number that was reported by the Vietnam National Administration of Tourism.

scholarly journals Business intelligence using the fuzzy-Kano model

2019 ◽  
Vol 9 (2) ◽  
Author(s):  
Soumaya Lamrharia ◽  
Hamid Elghazi ◽  
Abdellatif El Faker
Keyword(s):  
Customer Satisfaction ◽  
Business Intelligence ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Customer Requirements ◽  
Kano Model ◽  
The Voice ◽  
Allocation Approach ◽  
Voice Of The Customer ◽  
Dirichlet Allocation

Today, understanding customer satisfaction is becoming a difficult and complex task for companies due to the explosive growth of the voice of the customer in online reviews. This has pushed companies to rethink their business strategies and resort to business intelligence techniques in order to help them in analyzing customer requirements and market trends. This paper proposes a decision support framework for dynamically transforming the voice of the customer data into actionable insight. The framework measures the customer satisfaction by extracting key products’ aspects along with customers’ sentiments from online reviews using a text mining technique: the latent Dirichlet allocation approach. We apply the Fuzzy-Kano model to classify the real customer requirements, then, map them dynamically to the SWOT matrix. The proposed approach is extensively tested on an empirical dataset based on several performance metrics including accuracy, precision, recall, and F-score. The reported results showed that latent Dirichlet allocation approach has correctly extracted aspects with 97.4% accuracy and 92.4 % precision.

Mining numerical measure of consumers’ product evaluation expressed in words based on latent Dirichlet allocation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ziang Wang ◽  
Feng Yang
Keyword(s):  
Latent Dirichlet Allocation ◽  
Product Evaluation ◽  
Online Reviews ◽  
Product Evaluations ◽  
Product Attributes ◽  
Data Set ◽  
Content Type ◽  
Face To Face ◽  
Online Retailers ◽  
Dirichlet Allocation

Purpose It has always been a hot topic for online retailers to obtain consumers’ product evaluations from massive online reviews. In the process of online shopping, there is no face-to-face interaction between online retailers and customers. After collecting online reviews left by customers, online retailers are eager to acquire answers to some questions. For example, which product attributes will attract consumers? Or which step brings a better experience to consumers during the process of shopping? This paper aims to associate the latent Dirichlet allocation (LDA) model with the consumers’ attitude and provides a method to calculate the numerical measure of consumers’ product evaluation expressed in each word. Design/methodology/approach First, all possible pairs of reviews are organized as a document to build the corpus. After that, latent topics of the traditional LDA model noted as the standard LDA model, are separated into shared and differential topics. Then, the authors associate the model with consumers’ attitudes toward each review which is distinguished as positive review and non-positive review. The product evaluation reflected in consumers’ binary attitude is expanded to each word that appeared in the corpus. Finally, a variational optimization is introduced to calculate parameters mentioned in the expanded LDA model. Findings The experiment’s result illustrates that the LDA model in the research noted as an expanded LDA model, can successfully assign sufficient probability with words related to products attributes or consumers’ product evaluation. Compared with the standard LDA model, the expanded model intended to assign higher probability with words, which have a higher ranking within each topic. Besides, the expanded model also has higher precision on the prediction set, which shows that breaking down the topics into two categories fits better on the data set than the standard LDA model. The product evaluation of each word is calculated by the expanded model and depicted at the end of the experiment. Originality/value This research provides a new method to calculate consumers’ product evaluation from reviews in the level of words. Words may be used to describe product attributes or consumers’ experiences in reviews. Assigning words with numerical measures can analyze consumers’ products evaluation quantitatively. Besides, words are labeled themselves, they can also be ranked if a numerical measure is given. Online retailers can benefit from the result for label choosing, advertising or product recommendation.

scholarly journals Research on the Influence of E-commerce service quality of fresh Agricultural products on customer satisfaction

2020 ◽  
Vol 189 ◽  
pp. 01022
Author(s):  
Xu xin ◽  
Chen jiaying
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Significant Influence ◽  
Online Reviews ◽  
Service Level ◽  
Competitive Advantages ◽  
Web Crawler ◽  
Evaluation Indexes ◽  
Healthy Development

Analyzing the influence of service quality on customer satisfaction can help fresh e-commerce enterprises to better understand their own service level, formulate better service strategies and improve their competitive advantages, so as to promote the sustainable and healthy development of fresh e-commerce industry. In this paper, first of all, with the aid of web crawler, acquisition of jingdong mall fresh category contains fruit, vegetables, meat and seafood aquaculture 4 products on the number of online comments and evaluation star, and word frequency statistics and extract the data collected from online reviews of consumers to pay attention to the quality of service measures, after using qualitative analysis software - NVivo coding and grade, finally, the variable of descriptive statistics, correlation analysis and regression analysis. The results show that the tangibility, reliability, empathy and responsiveness of service quality have significant influence on customer satisfaction, and other evaluation indexes of guarantee quality have significant influence on customer satisfaction except delivery.

Looking beyond the stars: A description of text mining technique to extract latent dimensions from online product reviews

2019 ◽  
Vol 62 (2) ◽  
pp. 195-215
Author(s):  
Frederik Situmeang ◽  
Nelleke de Boer ◽  
Austin Zhang
Keyword(s):  
Text Mining ◽  
Customer Satisfaction ◽  
Research Methodology ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Product Reviews ◽  
Marketing Literature ◽  
Mining Technique ◽  
Online Product Reviews ◽  
The Relationship

The purpose of this study is to contribute to the marketing literature and practice by describing a research methodology to identify latent dimensions of customer satisfaction in product reviews, and examining the relationship between these attributes and customer satisfaction. Previous research in product reviews has largely relied only on quantitative ratings, either stars or review score. Advanced techniques for text mining provide the opportunity to extract meaning from customer online reviews. By analyzing 51,110 online reviews for 1,610 restaurants via latent Dirichlet allocation, this study uncovers 30 latent dimensions that are determinants of customer satisfaction. Furthermore, this study developed measurements of sentiment and innovativeness as moderators of the effect of these latent attributes to satisfaction.

scholarly journals Enhanced Twofold-LDA Model for Aspect Discovery and Sentiment Classification

2019 ◽  
Vol 9 (4) ◽  
pp. 1-20 ◽  
Author(s):  
Nicola Burns ◽  
Yaxin Bi ◽  
Hui Wang ◽  
Terry Anderson
Keyword(s):  
Domain Knowledge ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Classification Performance ◽  
The State ◽  
Sentiment Classification ◽  
Sentence Level ◽  
Dirichlet Allocation

There is a need to automatically classify information from online reviews. Customers want to know useful information about different aspects of a product or service and also the sentiment expressed towards each aspect. This article proposes an Enhanced Twofold-LDA model (Latent Dirichlet Allocation), in which one LDA is used for aspect assignment and another is used for sentiment classification, aiming to automatically determine aspect and sentiment. The enhanced model incorporates domain knowledge (i.e., seed words) to produce more focused topics and has the ability to handle two aspects in at the sentence level simultaneously. The experiment results show that the Enhanced Twofold-LDA model is able to produce topics more related to aspects in comparison to the state of arts method ASUM (Aspect and Sentiment Unification Model), whereas comparable with ASUM on sentiment classification performance.

Automated Keyword Filtering in LDA for Identifying Product Attributes from Online Reviews

2020 ◽  
pp. 1-10
Author(s):  
Junegak Joung ◽  
Harrison M. Kim
Keyword(s):  
Product Design ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Previous Method ◽  
Product Attributes ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Dirichlet Allocation

Abstract Identifying product attributes from the perspective of a customer is essential to measure the satisfaction, importance, and Kano category of each product attribute for product design. This paper proposes automated keyword filtering to identify product attributes from online customer reviews based on latent Dirichlet allocation. The preprocessing for latent Dirichlet allocation is important because it affects the results of topic modeling; however, previous research performed latent Dirichlet allocation either without removing noise keywords or by manually eliminating them. The proposed method improves the preprocessing for latent Dirichlet allocation by conducting automated filtering to remove the noise keywords that are not related to the product. A case study of Android smartphones is performed to validate the proposed method. The performance of the latent Dirichlet allocation by the proposed method is compared to that of a previous method, and according to the latent Dirichlet allocation results, the former exhibits a higher performance than the latter.

scholarly journals Analysis of Receptionist Service Quality to Increase Guest Satisfaction at Hotel Yusro Jombang

2021 ◽  
Vol 3 (2) ◽  
pp. 58-58
Author(s):  
Risa Hani Safitri ◽  
◽  
I Gusti Agung Bagus Mataram ◽  
I Putu Krisna Arta Widana ◽  
◽  
...  
Keyword(s):  
Performance Analysis ◽  
Data Collection ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Primary Data ◽  
Quality Level ◽  
Validity And Reliability ◽  
Satisfaction Index ◽  
Customer Satisfaction Index ◽  
Guest Satisfaction

This study aimed to analyze the level of receptionist service quality in increasing guest satisfaction at Hotel Yusro Jombang, East Java. The number of samples used was 60 respondents, with a purposive sampling data collection technique. The primary data collection method for service quality variables is using a questionnaire that has been tested for its validity and reliability. The analysis technique used is Customer Satisfaction Index, Servqual, and Importance Performance Analysis, presented in a Cartesian diagram. This study indicates that there is a negative, positive and neutral gap between guest perceptions and expectations. Customers are satisfied with the services provided because the value of the positive gap is more than the negative. The quality level of receptionist service in improving guest satisfaction at Hotel Yusro Jombang has been good, because the value of customer satisfaction index (CSI) of 90.22% is in the range of 81%-100%, meaning, in general, the guest satisfaction index at Hotel Yusro Jombang is on the "very satisfied" criteria. Next, based on the result of importance-performance analysis, each indicator's position in the cartesius diagram found an indicator that is a priority to be fixed, i.e., indicator in the A quadrant and an indicator that is an achievement to be maintained indicator which is in the B quadrant. As for indicators that are considered most satisfying by guests, they are X3 indicators, X5 indicators, and X10 indicators, each of them has a score of 0.04.

scholarly journals Influence of Online Reviews on Student Satisfaction Seen through a Service Quality Model

2021 ◽  
Vol 16 (7) ◽  
pp. 3063-3077
Author(s):  
Mostafa Torabi ◽  
Charles H. Bélanger
Keyword(s):  
Social Media ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Student Satisfaction ◽  
Word Of Mouth ◽  
Online Reviews ◽  
University Management ◽  
Quality Factors ◽  
Quality Model ◽  
The Impact

University or college is a challenging reality leading to a sometimes elusive career path. By consulting social media and review websites, students have more alternatives to consider in their choice determination. This study develops a multifaceted model to recognize the influence of service quality and e-word of mouth on customer satisfaction and the impact of customer satisfaction on word of mouth. Data gathered from a sample of 150 university students are analyzed by SPSS and PLS-SEM. The findings indicate that service quality dimensions and e-WOM have positive impacts on customer satisfaction. Furthermore, this study reinforces that customer satisfaction has a positive influence on customers’ WOM intentions. This research recommends that university management should consider the importance of service quality factors and social media channels to meet and exceed students’ expectations in order to bolster the quality of services and boost customer satisfaction.

Sign in / Sign up

Export Citation Format

Share Document