Cross-Cultural Comparisons of Review Aspect Importance

Previous text mining studies identified key common aspects in online restaurant reviews. However, it is not clear how important these aspects are for consumers. In this exploratory study, we used Yelp restaurant reviews on an ethnic food item, ramen noodles, and assessed the importance of each aspect to both U.S. and Japanese consumers. The results show that food and atmosphere are far more important than the other common aspects in both the U.S. and Japan. However, we found noticeable differences between consumers in the two countries regarding how the food aspect plays a role on star ratings. Both implications and a future research agenda are discussed

In search of negativity bias:An empirical study of perceived helpfulness of online reviews

A basic tenet of psychology is that the psychological effects of negative information outweigh those of positive information. Three empirical studies show that the negativity bias can be attenuated or even reversed in the context of electronic word-of-mouth (eWoM). The first study analyzes a large sample of customer reviews collected from Amazon.com and concludes that negative reviews are no more helpful than positive ones when controlling for review quality The second study follows up with a virtual experiment that confirms the lack of negativity bias in evaluating the helpfulness of online reviews. The third study demonstrates that the negativity effect can be reversed by manipulating the baseline valences. This work challenges the conventional wisdom of “bad is stronger than good” and contributes to the understanding of the eWoM phenomenon

Research on Hotel Management System

With rapid growth of economy and tourism, there is an intensified competition can be seen in the hotel industry in today. To be in the competition, they need to continuously improve their management techniques and procedures. “Online Hotel Management system” is software developed by focus on these factors. Through this system, it will be able to manage various functions including room and hall reservations, ordering food, and managing employees and suppliers. We intend to develop this web application using React JS, Express JS, Node JS, and Mongo DB. This system addresses hotel management issues while avoiding issues that arise when tasks are carried out manually. In terms, the main objective of this whole process is to automate the day today manual tasks of this system. Therefore, this online hotel management system is designed to find a more practical, well-organized, and quick way of processing the service from the hotel for both nearby and distant customers by giving more user friendly and more GUI oriented experience

Exploring Tourist Dining Preferences Based on Restaurant Reviews

Dining is an essential tourism component that attracts significant expenditure from tourists. Tourism practitioners need insights into the dining behaviors of tourists to support their strategic planning and decision making. Traditional surveys and questionnaires are time consuming and inefficient in capturing the complex dining behaviors of tourists at a large scale. Thus far, the understanding about the dining preferences and opinions of different tourist groups is limited. This article aims to fill the void by presenting a method that utilizes online restaurant reviews and text processing techniques in analyzing the dining behaviors of tourists. The effectiveness of the proposed method is demonstrated in a case study on international tourists visiting Australia using a large-scale data set of more than 40,000 restaurant reviews made by tourists on 2,265 restaurants. The proposed method can help researchers gain comprehensive insights into the dining preferences of tourists. </jats:p

Cross-Cultural Examination on Content Bias and Helpfulness of Online Reviews: Sentiment Balance at the Aspect Level for a Subjective Good

Online reviews can be fraught with biases, especially on experience goods. Using multilingual sentiment analysis software, we examined the characteristics of review biases and helpfulness at the aspect level across two different cultures. First, we found the lopsidedness of emotions expressed over the four key aspects of Japanese restaurant reviews between Japanese and Western consumers. Second, helpful reviews have sentiments expressed more evenly over those aspects than average for both Japanese and Western consumers. Third, however, there are significant differences over how sentiments are spread over aspects between them. Westerners found reviews helpful when reviews focused less on food and more on service. In addition, Japanese customers were more concerned with savings whereas Westerners paid attention to whether they are getting their money’s worth. These findings point to future research opportunities for leveraging sentiment analysis over key aspects of goods, particularly those of experience/subjective goods, across different cultures and customer profile categories

A Comparison of The Effectiveness of Various Social Media Platforms in Promoting Restaurants

The primary focus of this research is on how social media impacts the Colombian restaurant industry. Social media, without a question, has a significant impact on today's youth. Social media has a significant impact on a wide range of human activities. Using social media, such as Facebook, Instagram, and Twitter has a significant influence on the behavior of many people. Despite this, little is known about the impact of social media on the restaurant industry. In addition to fashion, entertainment, and eating habits, there are several other things that may be affected by social media. Social media's impact on Colombian eateries was examined in this research. Five eateries in Colombia's capital city of Bogota were found through an internet search that included a glance at their social media pages. This study's evidence was matched to the data from these social media accounts as part of a literature review. This document outlines the study's recommendations and limitations. Social media may help restaurants in Colombia run more efficiently and generate more money if utilized appropriately, according to the study

Meal Experiences at fine dining venues in Norway: A TripAdvisor case study

Purpose: Guest experience and feedback play a crucial role in ameliorating the quality of restaurant businesses. Despite their importance in the service sector, there has been little research on customer satisfaction in the restaurant industry in Norway. This study was conducted to identify the key attributes of the best restaurant experiences in Norway. Methods: A total of 714 online reviews of eight Norwegian luxury restaurants on TripAdvisor were used for data analysis in this study. A mixed methods approach was adopted to identify and determine the key quality attributes that influence diners’ experiences. Dominant themes for data analysis were identified and analyzed using Leximancer 5.0. Results: Nine themes (respectively in descending order of their influence): food, restaurant, experience, price, table (allocation), recommended, dessert, sea (food), and return were identified as the most important factors affecting guests’ dining experience. Concepts such as gourmet cuisine, courteous service, and memorable experience were frequently mentioned by satisfied guests, whereas pricing, service quality, and a perceived lack of innovation were the major factors among dissatisfied groups. Gastronomic components such as food, menu, and cuisine were the main factors affecting men's satisfaction, while evening, experience, and dishes were strongly associated with women's narratives. Similarly, the geographical origin and travel persona of the guests were attributable to the difference in their narratives and concepts. Originality/Value: The findings of this study highlight the overall satisfaction among visitors to the restaurants studied. The impressions and narratives of the guests are decisive for the overall success of the business. Therefore, restaurants should acknowledge their differences (in choices) and strive to achieve a higher level of satisfaction. Keywords: Meal Experience; Fine Dining; Online Reviews; Content Analysis; Leximancer

A comparative analysis of recommender systems based on item aspect opinions extracted from user reviews

In popular applications such as e-commerce sites and social media, users provide online reviews giving personal opinions about a wide array of items, such as products, services and people. These reviews are usually in the form of free text, and represent a rich source of information about the users’ preferences. Among the information elements that can be extracted from reviews, opinions about particular item aspects (i.e., characteristics, attributes or components) have been shown to be effective for user modeling and personalized recommendation. In this paper, we investigate the aspect-based recommendation problem by separately addressing three tasks, namely identifying references to item aspects in user reviews, classifying the sentiment orientation of the opinions about such aspects in the reviews, and exploiting the extracted aspect opinion information to provide enhanced recommendations. Differently to previous work, we integrate and empirically evaluate several state-of-the-art and novel methods for each of the above tasks. We conduct extensive experiments on standard datasets and several domains, analyzing distinct recommendation quality metrics and characteristics of the datasets, domains and extracted aspects. As a result of our investigation, we not only derive conclusions about which combination of methods is most appropriate according to the above issues, but also provide a number of valuable resources for opinion mining and recommendation purposes, such as domain aspect vocabularies and domain-dependent, aspect-level lexiconsThis work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (TIN2016-80630-P)