• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1489-1497
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• 2018

The importance of comments is constantly growing as a participation of individual in Online News that being invigorated. The 'Best Comments', which strongly related by major participants are recognized as a primary public opinion, and obtains the power. Thus this study is aimed to analyze the characteristics of the 'Best Comments' by utilizing the data of comments on Online News. For this study, a possible element that may reveal the difference between 'general' comments and 'best' comments were set up, digitalized the data, and examined the difference between 'general' and 'best' comments. This study is expected to provide a clue for the problematic issues, such as 'online comment rigged scandal' in recent; also as a basic data that subjected by the individual, academic society, government, and etc.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.513-524
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• 2020

Recently, YouTube's growth started drawing attention. YouTube is not only a content-consumption channel but also provides a space for consumers to express their intention. Consumers share their opinions on YouTube through comments. The study focuses on the text of global entrepreneurs' speeches and the comments in response to those speeches on YouTube. A content analysis was conducted for each speech and comment using the text mining software Leximancer. We analyzed the theme of each entrepreneurial speech and derived topics related to the propensity and characteristics of individual entrepreneurs. In the comments, we found the theme of money, work and need to be common regardless of the content of each speech. Talking into account the different lengths of text, we additionally performed a Prominence Index analysis. We derived time, future, better, best, change, life, business, and need as common keywords for speech contents and viewer comments. Users who watched an entrepreneur's speech on YouTube responded equally to the topics of life, time, future, customer needs, and positive change.

• Journal of Service Research and Studies
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• v.11 no.3
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• pp.1-16
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• 2021

Recently, crowdfunding has been receiving increased attention due to the variety of novel ways it provides for connecting funders and fundraisers. Concurrently, however, it has been criticized on the grounds of information asymmetry. We are interested in whether information collected from an asymmetric information source significantly influences crowdfunding success. Through this study, we would like to establish a social field of convergence pursued by Serve Science and to conduct practical research and practice together. First, we investigated the importance of interaction between funders and fundraisers within the crowdfunding platform. In the "comments" section, communication between funders and fundraisers reduces the degree of asymmetric information. In the aspect of presumable funders, they should make the best of the "comments" section to collect more solid information without losing return on their investment. Second, we analyze sentiment-based optimistic and pessimistic information from the "story" (asymmetric source) and "comments" sections. In conclusion, it shows that the optimistic and pessimistic information of the "comments" section has a great impact on crowdfunding success and that the influence of the "story" section is limited to pessimistic information under certain conditions. The crowdfunding platform is an innovative and productive way for startups and entrepreneurs to start a business, and since information an important role in the success of crowdfunding, It can be seen that it is essential to focus on establishing the best communication methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.641-651
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• 2023

Malicious hate speech and gender bias comments are common in online communities, causing social problems in our society. Gender bias and hate speech detection has been investigated. However, it is difficult because there are diverse ways to express them in words. To solve this problem, we attempted to detect malicious comments in a Korean hate speech dataset constructed in 2020. We explored bidirectional encoder representations from transformers (BERT)-based deep learning models utilizing hyperparameter tuning, data sampling, and logits ensembles with a label distribution. We evaluated our model in Kaggle competitions for gender bias, general bias, and hate speech detection. For gender bias detection, an F1-score of 0.7711 was achieved using an ensemble of the Soongsil-BERT and KcELECTRA models. The general bias task included the gender bias task, and the ensemble model achieved the best F1-score of 0.7166.

• Journal of Chest Surgery
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• v.45 no.4
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• pp.213-224
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• 2012

Tetralogy of Fallot (TOF) is an index lesion for all paediatric and congenital heart surgeons. In designing an appropriate operation for children with TOF, the predicted postoperative physiology must be taken into account, both for the short and long term. A favourable balance between pulmonary stenosis (PS) and pulmonary insufficiency (PI) may be critical for preservation of biventricular function. A unified repair strategy to limit both residual PS and PI is presented, along with supportive experimental evidence. A strategy for dealing with coronary anomalies and some comments regarding best timing of operation are also included.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.177-193
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• 2015

A great number of customers, who want to watch movies usually check out online reviews before choosing what to watch a movie. The most representative online media that customers consult are portal sites and SNS (Social Network Service). Although there have been numerous studies on online eWOM (e-Word of Mouth) and the effects of online media in businesses, it remains a question that which media is best for WOM (Word of Mouth) when selecting movies. This research examines customer's intention for consulting eWOM and for watching movies according to the number and tendency of online replies. We have compared portal sites and SNS about information of movie. The study shows that a large number of positive replies can affect the intention for WOM and choosing movies. Facebook has more influence than portal sites when choosing what to watch when replies consist of large and positive comments. However, there is no difference between the two types of media when they consist of negative comments.

• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.2
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• pp.71-92
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• 1995

This study Is about the situation of contemporary landscape architecture design in Korea. The conceptual framework of interpretation for landscape architectural works is formulated to define the design trends of today′s professional works The study′s analytical method is composed of the survey of attitudes questionnaire, the analysis of design composition techniques and conclusions drawn from the comments of contemporary landscape architectural critics. Among 975 members of the Korean Institute of Landscape Architecture, 318 professionals responded to the survey questionnaire. The survey revealed that landscape architects in Korea are concerned about the profession′s reduced contributions to the sharping of the built environment. However, they are optimistic about its future. Ten top design works were selected from the surveys′ answers and were analyzed for the design characteristics which could best represent the trends of the last thirty years. Several design critiques and comments about the professional works were cited to reinforce the outlined "-ty" of the contemporary design phenomena. The study identified the following distinguished design trends of contemporary Korean landscape architectural works They are as follows: Themelessty, Powerity, Traditionality, Monumentality, Non-contextuality and Over-designity. These trends identify the overall prevailing conditions of Korean landscape architectural design over the past thirty years.

• Journal of the Korean Society of Food Culture
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• v.34 no.2
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• pp.184-200
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• 2019

This study aims to establish a strategy for selling kimchi to satisfy the needs and wants of European consumers through survey, FGI, and IDI. All survey participants were Europeans and were selected on the basis of their kimchi awareness. For the quantitative survey, 246 participants 15 years or older were selected; for FGI, 33 participants aged between 20 and 49 were selected; and for IDI, eight chefs were selected. The survey included four steps of 'Awareness-First try-Needs-Future consumption'. The participants got to know kimchi through the Internet; for example, by visiting Korea and Hallyu, and suggested positive comments, including 'fancy' and 'exotic.' While satisfaction with kimchi sharply decreased due to taste and appearance in the first try of kimchi, it is important to provide the best first-try experience. It also showed that important needs for kimchi are 'hot sensation', 'crunchiness' and 'presentation'. They gave a negative answer to combination with traditional cuisines of their own country, but provided positive comments for benchmarking the use of traditional pickled foods. This study suggests that it may be necessary to implement a two-track strategy by the traditional kimchi as a 'strategic product' and localized kimchi as a 'key product'.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.189-200
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• 2022

The gig economy offers many advantages, such as flexibility, variety, independence, and lower cost. However, there are also safety concerns, lack of regulations, uncertainty, and unsatisfactory services, causing people to voice their opinion on social media. This paper aims to explore the sentiments of consumers concerning gig economy services (Grab, Foodpanda and Airbnb) through the analysis of social media. First, Vader Lexicon was used to classify the comments into positive, negative, and neutral sentiments. Then, the comments were further classified into three machine learning algorithms: Support Vector Machine, Light Gradient Boosted Machine, and Logistic Regression. Results suggested that gig economy services in Malaysia received more positive sentiments (52%) than negative sentiments (19%) and neutral sentiments (29%). Based on the three algorithms used in this research, LGBM has been the best model with the highest accuracy of 85%, while SVM has 84% and LR 82%. The results of this study proved the power of text mining and sentiment analysis in extracting business value and providing insight to businesses. Additionally, it aids gig managers and service providers in understanding clients' sentiments about their goods and services and making necessary adjustments to optimize satisfaction.