Exploring the generalizability of discriminant word items and latent topics in online tourist reviews

2017 ◽  
Vol 29 (2) ◽  
pp. 803-816 ◽  
Author(s):  
Astrid Dickinger ◽  
Lidija Lalicic ◽  
Josef Mazanec
Keyword(s):  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Support Vector ◽  
Content Type ◽  
Tourism Management ◽  
Hospitality And Tourism Management ◽  
Vector Machines ◽  
Latent Topics ◽  
Review Reports ◽  
Limited Generalizability

Purpose Online reviews have been gaining relevance in hospitality and tourism management and represent an important research avenue for academia. This study aims to illustrate the discrimination between positive and negative reviews based on single word items and the sector-specific relevance of hidden topics. Design/methodology/approach By probing two parallel approaches of entirely unrelated analytical methods (penalized support vector machines and Latent Dirichlet Allocation), the analysts explore differences in language between favorable and unfavorable reviews in three service settings (hotels, restaurants and attractions). Findings The percentage of correctly predicted positive and negative review reports by means of individual word items does not decrease if reports from the three tourism businesses are analyzed together. Originality/value However, there is limited generalizability of the discriminant words across the three businesses. Also, the latent topics relevant for generating customers’ review reports differ significantly between the three sectors of tourism businesses.

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.

Credit risk assessment for unbalanced datasets based on data mining, artificial neural network and support vector machines

2018 ◽  
Vol 13 (4) ◽  
pp. 932-951 ◽  
Author(s):  
Sihem Khemakhem ◽  
Fatma Ben Said ◽  
Younes Boujelbene
Keyword(s):  
Support Vector Machines ◽  
Credit Risk ◽  
Characteristic Curve ◽  
Confusion Matrix ◽  
Statistical Prediction ◽  
Support Vector ◽  
Sampling Strategies ◽  
Content Type ◽  
Vector Machines ◽  
Artificial Neural

Purpose Credit scoring datasets are generally unbalanced. The number of repaid loans is higher than that of defaulted ones. Therefore, the classification of these data is biased toward the majority class, which practically means that it tends to attribute a mistaken “good borrower” status even to “very risky borrowers”. In addition to the use of statistics and machine learning classifiers, this paper aims to explore the relevance and performance of sampling models combined with statistical prediction and artificial intelligence techniques to predict and quantify the default probability based on real-world credit data. Design/methodology/approach A real database from a Tunisian commercial bank was used and unbalanced data issues were addressed by the random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). Performance was evaluated in terms of the confusion matrix and the receiver operating characteristic curve. Findings The results indicated that the combination of intelligent and statistical techniques and re-sampling approaches are promising for the default rate management and provide accurate credit risk estimates. Originality/value This paper empirically investigates the effectiveness of ROS and SMOTE in combination with logistic regression, artificial neural networks and support vector machines. The authors address the role of sampling strategies in the Tunisian credit market and its impact on credit risk. These sampling strategies may help financial institutions to reduce the erroneous classification costs in comparison with the unbalanced original data and may serve as a means for improving the bank’s performance and competitiveness.

scholarly journals Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp

2019 ◽  
Vol 11 (19) ◽  
pp. 5254 ◽  
Author(s):  
Yi Luo ◽  
Xiaowei Xu
Keyword(s):  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Restaurant Industry ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Plain Text ◽  
Sustainable Marketing ◽  
Restaurant Reviews ◽  
Negative Sentiment ◽  
Sustainable Competitive Advantages

Helpful online reviews could be utilized to create sustainable marketing strategies in the restaurant industry, which contributes to national sustainable economic development. This study, the main aspects (including food/taste, experience, location, and value) from 294,034 reviews on Yelp.com were extracted empirically using the Latent Dirichlet Allocation (LDA) and positive and negative sentiment were assigned to each extracted aspect. Positive sentiments were associated with food/taste, while negative sentiments were associated with value. This study further proves a robust classification algorithm based on Support Vector Machine (SVM) with a Fuzzy Domain Ontology (FDO) algorithm outperforms other traditional classification algorithms such as Naïve Bayes (MB) and SVM ontology in predicting the helpfulness of online reviews. This study enriches the literature on managerial aspects of sustainability by analyzing a large amount of plain text data that customers generated. The results of this study could be used as sustainable marketing strategy for review website developers to design sophisticated, intelligence review systems by enabling customers to sort and filter helpful reviews based on their preferences. The extracted aspects and their assigned sentiment could also help restaurateurs better understand how to meet diverse customers’ needs and maintain sustainable competitive advantages.

A new classification strategy for human activity recognition using cost sensitive support vector machines for imbalanced data

Kybernetes ◽  
2014 ◽  
Vol 43 (8) ◽  
pp. 1150-1164 ◽  
Author(s):  
Bilal M’hamed Abidine ◽  
Belkacem Fergani ◽  
Mourad Oussalah ◽  
Lamya Fergani
Keyword(s):  
Support Vector Machines ◽  
Probabilistic Models ◽  
Conditional Random Fields ◽  
Performance Metrics ◽  
Imbalanced Data ◽  
Sampling Technique ◽  
Support Vector ◽  
Data Set ◽  
Content Type ◽  
Vector Machines

Purpose – The task of identifying activity classes from sensor information in smart home is very challenging because of the imbalanced nature of such data set where some activities occur more frequently than others. Typically probabilistic models such as Hidden Markov Model (HMM) and Conditional Random Fields (CRF) are known as commonly employed for such purpose. The paper aims to discuss these issues. Design/methodology/approach – In this work, the authors propose a robust strategy combining the Synthetic Minority Over-sampling Technique (SMOTE) with Cost Sensitive Support Vector Machines (CS-SVM) with an adaptive tuning of cost parameter in order to handle imbalanced data problem. Findings – The results have demonstrated the usefulness of the approach through comparison with state of art of approaches including HMM, CRF, the traditional C-Support vector machines (C-SVM) and the Cost-Sensitive-SVM (CS-SVM) for classifying the activities using binary and ubiquitous sensors. Originality/value – Performance metrics in the experiment/simulation include Accuracy, Precision/Recall and F measure.

Resort-based or resource-based tourism? A case study of Jamaica

2014 ◽  
Vol 4 (2) ◽  
pp. 1-19 ◽  
Author(s):  
Gaunette Marie Sinclair-Maragh
Keyword(s):  
Learning Outcomes ◽  
Tourism Development ◽  
Tourism Industry ◽  
Content Type ◽  
Tourism Management ◽  
Hospitality And Tourism Management ◽  
The Future ◽  
Hospitality And Tourism

Title – Resort-based or resource-based tourism? A case study of Jamaica. Subject area – This case study can be used in the following subject areas: tourism management; tourism policy; tourism planning and development; destination marketing and management; hospitality and tourism management; special event planning and management; and attraction management. Study level/applicability – This case study is useful to both undergraduate and graduate students specializing in hospitality and tourism management. Case overview – This case study explored the nature of two forms of tourism development; resort-based and resource-based, and aimed to determine which is the more viable and sustainable option for the future of tourism in Jamaica, an island destination in the Caribbean which depends highly on the tourism industry. The literature established that both forms of tourism are challenged by several and varying factors and so their synergistic integration appears to be the most functional option for sustainable tourism development in Jamaica along with the involvement of the relevant stakeholders. Expected learning outcomes – The students should be able to: Distinguish between resort-based tourism and resource-based tourism by identifying the elements and attributes that make them different. ▪Explain the usefulness and drawbacks of both types of tourism model. ▪Discuss the nature of culture and heritage tourism and eco-tourism. ▪Analyze Jamaica's tourism model from the nineteenth to the twenty-firstst century by assessing the changes and developments. ▪Discuss the role of government in facilitating the development of a “wholisitic tourism model” that will facilitate the synergy of resort-based tourism and resource-based tourism. ▪Assess the role of the private sector in encouraging and facilitating resource-based tourism. Supplementary materials – Teaching notes are available for educators only. Please contact your library to gain login details or email [email protected] to request teaching notes. Social implications – This case study conceptually and empirically analyzed the tourism model in Jamaica to ascertain whether or not the future of Jamaica's tourism should remain dependent on resort-based tourism or should it opt for resource-based tourism as a more viable and sustainable option. The discussion however, indicates that resort-based tourism can synergize with resource-based tourism to achieve sustainable development along with the involvement of all the relevant stakeholders including the government, hotel operators and the residents. The case synopsis likewise presented a concise summary of the literature reviewed regarding the concepts of resort-based tourism and resource-based tourism; and the case of Jamaica's tourism.The learning outcomes are intended to guide the teaching- learning process and stimulate students' understanding of the concepts of resort-based tourism and resource-based tourism and their specific implications in terms of tourism development in Jamaica. This knowledge can also be generalized to other destinations with similar historical background and tourism resources. The applied questions will guide the discussions and provide additional resources for assessment purposes. They will also help the students to critically assess the dynamics of tourism development.The case synopsis is consistent with the learning outcomes, corresponding applied questions and course recommendations. A total of two to three-hours teaching session can be used to discuss the constructs, analyze the case in point and answer the applied questions.

Air Jamaica … more than a national airline

2011 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Gaunette Sinclair-Maragh
Keyword(s):  
Environmental Factors ◽  
Strategic Management ◽  
Economic Recession ◽  
Subject Area ◽  
Historical Background ◽  
Content Type ◽  
Tourism Management ◽  
Hospitality And Tourism Management ◽  
Hospitality And Tourism ◽  
The Government

Subject area Hospitality and tourism management; strategic management; marketing, transportation system management and human resource management. Study level/applicability Undergraduate in business and management and hospitality and tourism management. Case overview This teaching case outlines the historical background, successes and challenges of the national airline of Jamaica. It shows how a national airline, which is a heritage asset and one that has provided nostalgic and sentimental value to the Jamaican people and its passengers, had to be divested. The airline has been faced with several challenges; the major one being high-operating costs, especially in light of the global economic recession. The case also highlights the various procedures carried out by the Government of Jamaica before and after the divestment arrangement and also by the acquirer, Caribbean Airlines. Expected learning outcomes The student should be able to: first, differentiate among the various strategic management terms and concepts used in the case; second, explain the importance of strategic decisions versus emotional decisions; third, assess the environmental factors that impacted Air Jamaica's operation; fourth, analyse the environmental factors that should have been considered by Caribbean Airlines before making the decision to acquire Air Jamaica; fifth, carry out a comparative analysis of the various corporate-level strategies to identify the best option for the Government of Jamaica; sixth, propose reasons why Caribbean Airlines acquired Air Jamaica. Supplementary materials Teaching note.

Optimizing parameters of support vector machines using team-search-based particle swarm optimization

2015 ◽  
Vol 32 (5) ◽  
pp. 1194-1213 ◽  
Author(s):  
Long Zhang ◽  
Jianhua Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Support Vector Machines ◽  
Search Strategy ◽  
Cross Validation ◽  
Particle Swarm ◽  
Parameter Tuning ◽  
Support Vector ◽  
Swarm Optimization ◽  
Content Type ◽  
Vector Machines

Purpose – It is greatly important to select the parameters for support vector machines (SVM), which is usually determined by cross-validation. However, the cross-validation is very time-consuming and complicated to create good parameters for SVM. The parameter tuning issue can be solved in the optimization framework. The paper aims to discuss these issues. Design/methodology/approach – In this paper, the authors propose a novel variant of particle swarm optimization (PSO) for the selection of parameters in SVM. The proposed algorithm is denoted as PSO-TS (PSO algorithm with team-search strategy), which is with team-based local search strategy and dynamic inertia factor. The ultimate design purpose of the strategy is to realize that the algorithm can be suitable for different problems with good balance between exploration and exploitation and efficiently control the inertia of the flight. In PSO-TS, the particles accomplish the assigned tasks according to different topology and detailedly search the achieved and potential regions. The authors also theoretically analyze the behavior of PSO-TS and demonstrate they can share the different information from their neighbors to maintain diversity for efficient search. Findings – The validation of PSO-TS is conducted over a widely used benchmark functions and applied to tuning the parameters of SVM. The experimental results demonstrate that the proposed algorithm can tune the parameters of SVM efficiently. Originality/value – The developed method is original.

scholarly journals A Recommendation Mechanism for Under-Emphasized Tourist Spots Using Topic Modeling and Sentiment Analysis

2019 ◽  
Vol 12 (1) ◽  
pp. 320 ◽  
Author(s):  
Wafa Shafqat ◽  
Yung-Cheol Byun
Keyword(s):  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Recommendation Systems ◽  
Support Vector ◽  
Latent Factors ◽  
Internet Applications ◽  
Enormous Amount ◽  
Combined Features ◽  
Latent Topics ◽  
User History

With rapid advancements in internet applications, the growth rate of recommendation systems for tourists has skyrocketed. This has generated an enormous amount of travel-based data in the form of reviews, blogs, and ratings. However, most recommendation systems only recommend the top-rated places. Along with the top-ranked places, we aim to discover places that are often ignored by tourists owing to lack of promotion or effective advertising, referred to as under-emphasized locations. In this study, we use all relevant data, such as travel blogs, ratings, and reviews, in order to obtain optimal recommendations. We also aim to discover the latent factors that need to be addressed, such as food, cleanliness, and opening hours, and recommend a tourist place based on user history data. In this study, we propose a cross mapping table approach based on the location’s popularity, ratings, latent topics, and sentiments. An objective function for recommendation optimization is formulated based on these mappings. The baseline algorithms are latent Dirichlet allocation (LDA) and support vector machine (SVM). Our results show that the combined features of LDA, SVM, ratings, and cross mappings are conducive to enhanced performance. The main motivation of this study was to help tourist industries to direct more attention towards designing effective promotional activities for under-emphasized locations.

scholarly journals Gender research in hospitality and tourism management: time to change the guard

2020 ◽  
Vol 32 (5) ◽  
pp. 1861-1879 ◽  
Author(s):  
Shelagh K. Mooney
Keyword(s):  
Queer Theory ◽  
Gender Studies ◽  
Gender Discrimination ◽  
Diversity Management ◽  
Content Type ◽  
Gender Research ◽  
Tourism Management ◽  
Gender Diverse ◽  
Hospitality And Tourism Management ◽  
Hospitality And Tourism

Purpose The purpose of this paper is to explain the problem with how gender is positioned in hospitality and tourism management studies. It recommends critical theories to investigate how gender is researched in the sector’s academic and institutional systems. Design/methodology/approach The conceptual study explains contemporary gender theories and gives examples of relevant hospitality and tourism management studies. A four point critical agenda for researching gender is proposed and justified. Findings The study highlights how the focus on “female leadership” as different from the male norm and the use of traditional theoretical framings reinforce stereotypes about the primacy of women’s domestic commitments to their detriment. Research limitations/implications A limitation of this academy focussed study is that it has not recommended specific initiatives to combat specific issues of gender discrimination in hospitality and tourism employment. A further limitation is that the primary focus was on critical management theory to explain heteronormative based gender discrimination. It did not discuss queer theory. Practical implications In addition, a new research agenda, steps are proposed to change the masculine culture. Hospitality and tourism universities and research institutions should review men’s/women’s/gender diverse representation at leadership levels. Critical gender research approaches may also be fostered by sectorial conference streams and journal special issues and university graduate research students should be taught to design such studies. Social implications The use of contemporary approaches in gender studies will enable researchers to propose more targeted equality and diversity management actions for industry. They will also assist educators to better design curricula that protect and promote the interests of women studying a hospitality, tourism or events degree and those who identify as gender diverse. Originality/value The paper challenges the masculine status quo in hospitality and tourism management gender studies, arguing that adherence to traditional orthodoxies has stifled the development of critical paradigms and methodologies. Its key contribution is to reveal the advantages that critical gender theorising can bring to further the aim of gender equality by showing practical applications.

Automatic evaluation of online learning interaction content using domain concepts

2020 ◽  
Vol 38 (3) ◽  
pp. 421-445
Author(s):  
Di Wu ◽  
Lei Wu ◽  
Alexis Palmer ◽  
Dr Kinshuk ◽  
Peng Zhou
Keyword(s):  
Online Learning ◽  
Online Course ◽  
Support Vector ◽  
Content Type ◽  
Educational Domain ◽  
Novel Approach ◽  
Vector Machines ◽  
Quality Dimensions ◽  
Supporting Teachers

Purpose Interaction content is created during online learning interaction for the exchanged information to convey experience and share knowledge. Prior studies have mainly focused on the quantity of online learning interaction content (OLIC) from the perspective of types or frequency, resulting in a limited analysis of the quality of OLIC. Domain concepts as the highest form of interaction are shown as entities or things that are particularly relevant to the educational domain of an online course. The purpose of this paper is to explore a new method to evaluate the quality of OLIC using domain concepts. Design/methodology/approach This paper proposes a novel approach to automatically evaluate the quality of OLIC regarding relevance, completeness and usefulness. A sample of OLIC corpus is classified and evaluated based on domain concepts and textual features. Findings Experimental results show that random forest classifiers not only outperform logistic regression and support vector machines but also their performance is improved by considering the quality dimensions of relevance and completeness. In addition, domain concepts contribute to improving the performance of evaluating OLIC. Research limitations/implications This paper adopts a limited sample to train the classification models. It has great benefits in monitoring students’ knowledge performance, supporting teachers’ decision-making and even enhancing the efficiency of school management. Originality/value This study extends the research of domain concepts in quality evaluation, especially in the online learning domain. It also has great potential for other domains.

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