• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.05a
• /
• pp.389-392
• /
• 2020

The growth in social media, blogs and restaurant listing directories have led to increasing customer reviews about restaurants, their quality of food items and services available on the internet. These user reviews offer a massive amount of valuable information that can be used for various decision-making purposes. Currently, most food recommendation sites provide recommendation scores about restaurants rather than food items of the restaurant and the provided recommendation scores may be biased since they are calculated only from user reviews listed only in their sites. Usually, people wants a reliable recommendation about foods, not restaurant. In this paper, we present a reliable Korean food items rating method; we first extract food items by applying NER technique to restaurant reviews collected from many Korean restaurant recommendation web sites, blogs and web data. Then, we apply lexicon-based sentiment analysis on collected user reviews and predict people's opinions as sentiment polarity scores (+1 for positive; -1 for negative; 0 for neutral). Finally, by taking average of all calculated polarity scores about a food item, we obtain a rating to individual menu items of the restaurant. The proposed food item rating is more reliable since it does not depend on reviews of only one site.

• Information Systems Review
• /
• v.24 no.3
• /
• pp.43-68
• /
• 2022

With the growing demand for online food delivery (OFD) services via Online to Offline (O2O) platforms, it is required for academic researchers to identify the success factors of OFD businesses. In line with this, this research examines the impact of the core service attributes of a restaurant (hygiene, interactivity, trust,and popularity) on business success in the OFD platform context from the perspective of information asymmetry. Furthermore, the moderating effects of hygiene factor between the core service attributes and the success of restaurants are evaluated. We utilize 1,146 restaurants registered on the largest OFD platform in Korea. The results of this study demonstrate that hygiene (certification), trust (franchise), popularity (favorite) factors have positive impacts on the success of OFD businesses. Moreover, we find that franchise restaurants with high response rates to customer reviews and inquiries achieve higher sales when they have hygiene certifications than those without the certification do. The key findings bear significant contributions to prior literature by empirically substantiating the pivotal role of service quality signals in fostering restaurant success on the OFD platforms. In addition, this study provides business implications for restaurants in O2O platform.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.115-130
• /
• 2011

Many online stores bring features that can build trust in their customers. More so, the number of products or content services on online stores has been increasing rapidly. Hence, personalization on online stores is considered to be an important technology to companies and customers. Recommender systems that provide favorable products and customer product reviews to users are the most commonly used features in this purpose. There are many studies to that investigated the relationship between social presence as an antecedent of trust and provision of recommender systems or customer product reviews. Many online stores have made efforts to increase perceived social presence of their customers through customer reviews, recommender systems, and analyzing associations among products. Primarily because social presence can increase customer trust or reuse intention for online stores. However, there were few studies that investigated the interactions between recommendation type, product type and provision of customer product reviews on social presence. Therefore, one of the purposes of this study is to identify the effects of personalized recommender systems and compare the role of customer reviews with product types. This study performed an experiment to see these interactions. Experimental web pages were developed with $2{\times}2$ factorial setting based on how to provide social presence to users with customer reviews and two product types such as hedonic and utilitarian. The hedonic type was a ringtone chosen from Nate.com while the utilitarian was a TOEIC study aid book selected from Yes24.com. To conduct the experiment, web based experiments were conducted for the participants who have been shopping on the online stores. Participants were a total of 240 and 30% of the participants had the chance of getting the presents. We found out that social presence increased for hedonic products when personalized recommendations were given compared to non.personalized recommendations. Although providing customer reviews for two product types did not significantly increase social presence, provision of customer product reviews for hedonic (ringtone) increased perceived social presence. Otherwise, provision of customer product reviews could not increase social presence when the systems recommend utilitarian products (TOEIC study.aid books). Therefore, it appears that the effects of increasing perceived social presence with customer reviews have a difference for product types. In short, the role of customer reviews could be different based on which product types were considered by customers when they are making a decision related to purchasing on the online stores. Additionally, there were no differences for increasing perceived social presence when providing customer reviews. Our participants might have focused on how recommendations had been provided and what products were recommended because our developed systems were providing recommendations after participants rating their preferences. Thus, the effects of customer reviews could appear more clearly if our participants had actual purchase opportunity for the recommendations. Personalized recommender systems can increase social presence of customers more than nonpersonalized recommender systems by using user preference. Online stores could find out how they can increase perceived social presence and satisfaction of their customers when customers want to find the proper products with recommender systems and customer reviews. In addition, the role of customer reviews of the personalized recommendations can be different based on types of the recommended products. Even if this study conducted two product types such as hedonic and utilitarian, the results revealed that customer reviews for hedonic increased social presence of customers more than customer reviews for utilitarian. Thus, online stores need to consider the role of providing customer reviews with highly personalized information based on their product types when they develop the personalized recommender systems.

• The Journal of Society for e-Business Studies
• /
• v.18 no.4
• /
• pp.315-326
• /
• 2013

Users in social media post various types of opinions such as product reviews and movie reviews. It is a common trend that customers get assistance from the opinions in making their decisions. However, as opinion usage grows, distorted feedbacks also have increased. For example, exaggerated positive opinions are posted for promoting target products. So are negative opinions which are far from common evaluations. Finding these biased opinions becomes important to keep social media reliable. Techniques of opinion mining (or sentiment analysis) have been developed to determine sentiment polarity of opinionated documents. These techniques can be utilized for finding the biased opinions. However, the previous techniques have some drawback. They categorize the text into only positive and negative, and they also need a large amount of training data to build the classifier. In this paper, we propose methods for discovering the biased opinions which are skewed from the overall common opinions. The methods are based on angle based outlier detection and personalized PageRank, which can be applied without training data. We analyze the performance of the proposed techniques by presenting experimental results on a movie review dataset.

• Journal of Software Engineering Society
• /
• v.27 no.1
• /
• pp.8-14
• /
• 2018

As cloud computing has emerged as a hot trend in the IT industry, various types of cloud services have emerged. In addition, cloud service broker (CSB) technology has emerged to alleviate the complexity of the process of selecting the desired service that user wants among the various cloud services. One of the key features of the CSB is to recommend the best cloud services to users. In general, CSB can use a method to evaluate a service by receiving feedback about a service from users in order to recommend a cloud service. However, since each user has different criteria for giving a rating, there is a problem that reliability of service evaluation can be low when the rating is only used. In this paper, a method is proposed to supplement evaluation of rating based service by applying machine learning based sentiment analysis to cloud service user's review. In addition, the CSB prototype is implemented based on proposed method. Further, the results of comparing the performance of various learning algorithms is proposed that can be used for sentiment analysis through experiments using actual cloud service review as learning data. The proposed service evaluation method complements the disadvantages of the existing rating-based service evaluation and can reflect the service quality in terms of user experience.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.2
• /
• pp.493-498
• /
• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.

• Korean journal of communication and information
• /
• v.37
• /
• pp.307-341
• /
• 2007

The Blog enables individuals to become communication producers, not merely consumers. This study aims to analyse the practice of the Blog communication and the surrounding social dynamics. Employing ethnographic content analysis, in-depth interview, and participatory observation, this study tried to explore following research questions: 1) What are the value-added process and social dynamics surrounding the production and practice of the Blog communication? From the perspective of political economy, the mechanisms of market economy of capitalism directly and indirectly worked in Blog production, making it as a medium for profit. The power of capital overwhelmed the blog. These results enable us to predict that Blog can be a new tool for capitalism to create profit.

• Journal of the Korean Magnetics Society
• /
• v.20 no.2
• /
• pp.75-82
• /
• 2010

A recent progress on the prediction of the thermal stability of a nanostructured exchange-coupled trilayer is reviewed. An analytical/numerical combined method is used to calculate its magnetic energy barrier and hence the thermal stability parameter. An important feature of the method is the use of an analytical equation for the total energy that contains the magnetostatic fields. Under an assumption of the single domain state, the effective values of all the magnetostatic fields can be obtained by averaging their nonuniform values over the entire magnetic volume. In an equilibrium state, however, it is not easy to calculate the magnetostatic fields at the saddle point due to the absence of suitable methods of the accessing its magnetic configuration. This difficulty is overcome with the use of equations that link the magnetostatic fields at the saddle point and critical fields. Since the critical fields can readily be obtained by micromagnetic simulation, the present method should provide accurate results for the thermal stability of a nanostructured exchange-coupled trilayer.

• The Journal of the Korea Contents Association
• /
• v.21 no.4
• /
• pp.1-13
• /
• 2021

With the global pandemic of COVID-19, it is pointed out that exposure to false information to the public could cause serious problems. However, in pandemic situations, there is also an positive effect for the public to share private-led information rather than centralized unilateral delivery of information. This study analyzes the role of private-led information provision in infectious disease situations. To this end, topic modeling and sentiment analysis is carried out on online reviews of all COVID-19-related applications in Google Playstore provided by the Korean government and the private. The results showed that the user's evaluation of private apps, which were used from the early stage of COVID-19, was much higher than the apps provided by the government. In particular, users responded more positively to private apps than government apps in all aspects such as reliability of information, risk avoidance, timeliness, usefulness, and stability. Based on these results, a post-monitoring system is recommended rather than a pre-block of all private apps.

• Cartoon and Animation Studies
• /
• s.37
• /
• pp.463-489
• /
• 2014

Virtually unanimous praise poured over him notwithstanding, critical discussions of Yeon Sang-ho's animation works largely remain amorphous. Except for scattered reviews, no serious work of engagement with his works has yet to exist. In seeking to fill this yawning void, this paper insists his works be treated as oeuvre. By analyzing the two animated features along with his shorts, I will show how radical Yeon's works remain vis-a-vis contemporary Korean society. At their narrative core, his works, I argue, revolve around the problem of solidarity, or lack thereof among the abjected people. In contradistinction to the critical common sense whereby the supposed continuity between the two works is casually bypassed, I insist on the peculiar ways in which both resonate with difference. Further, and perhaps more importantly, I will demonstrate how these otherwise merely thematic concerns are rendered formally in his animated works in terms of what I call "abyssal surface". Despite his allegedly "realistic" style, Yeon's works rather embody the utter lack/excess of trust among the abjected people as animation, i.e., ominously superficial surface beyond whose facade lurks abyssal lack/excess of mutual trust. Precisely in this double sense of the term, i.e., that thematically they touch on the roots of society, and, formally, those of animation as such, Yeon's animation works are radical.