• Smart Media Journal
• /
• v.12 no.11
• /
• pp.77-85
• /
• 2023

After COVID-19, communication through online platforms has increased, leading to an accumulation of massive amounts of conversational text data. With the growing importance of summarizing this text data to extract meaningful information, there has been active research on deep learning-based abstractive summarization. However, conversational data, compared to structured texts like news articles, often contains missing or transformed information, necessitating consideration from multiple perspectives due to its unique characteristics. In particular, vocabulary omissions and unrelated expressions in the conversation can hinder effective summarization. Therefore, in this study, we restructured by considering the characteristics of Korean conversational data, fine-tuning a pre-trained text summarization model based on KoBART, and improved conversation data summary perfomance through a refining operation to remove redundant elements from the summary. By restructuring the sentences based on the order of utterances and extracting a central speaker, we combined methods to restructure the conversation around them. As a result, there was about a 4 point improvement in the Rouge-1 score. This study has demonstrated the significance of our conversation restructuring approach, which considers the characteristics of dialogue, in enhancing Korean conversation summarization performance.

• Korean Journal of Radiology
• /
• v.23 no.8
• /
• pp.835-845
• /
• 2022

Objective: To analyze the characteristics and trends of scientific publications on thyroid ultrasound (US) from 2001 to 2020, specifically examining the differences among disciplines. Materials and Methods: The MEDLINE database was searched for scientific articles on thyroid US published between 2001 and 2020 using the PubMed online service. The evaluated parameters included year of publication, type of document, topic, funding, first author's specialty, journal name, subject category, impact factor, and quartile ranking of the publishing journal, country, and language. Relationships between the first author's specialty (radiology, internal medicine, surgery, otorhinolaryngology, and miscellaneous) and other parameters were analyzed. Results: A total of 2917 thyroid US publications were published between 2001 and 2020, which followed an exponential growth pattern, with an annual growth rate of 11.6%. Radiology produced the most publications (n = 1290, 44.2%), followed by internal medicine (n = 716, 24.5%), surgery (n = 409, 14.0%), and otorhinolaryngology (n = 171, 5.9%). Otorhinolaryngology and internal medicine published significantly more case reports than radiology (p < 0.001, each). Radiology published a significantly higher proportion of publications on imaging diagnosis (p < 0.001 for all) and a significantly lower proportion of publications on biopsy (p < 0.001 for all) than the other disciplines. Publications produced by radiology authors were less frequently published in Q1 journals than those from other disciplines (p < 0.005 for internal medicine and miscellaneous disciplines and < 0.01 for surgery and otorhinolaryngology). China contributed the greatest number of publications (n = 622, 21.3%), followed by South Korea (n = 478, 16.4%) and the United States (n = 468, 16.0%). Conclusion: Radiology produced the most publications for thyroid US than any other discipline. Radiology authors published more notably on imaging diagnosis compared to other topics and in journals with lower impact factors compared to authors in other disciplines.

• Journal of Ecology and Environment
• /
• v.48 no.2
• /
• pp.182-195
• /
• 2024

Background: Invasive alien plant species (IAP) significantly threaten Nepal's protected areas and local communities. Understanding their distribution, impact, management, and utilization is essential for developing effective management strategies and sustainable utilization practices. The systematic literature review of publications from 2010 to 2023. The search was conducted through the database Nepal Journal online database (NepJOL) and Google Scholar, yielding an initial pool of 4,304 publication. After applying inclusion and exclusion criteria; we meticulously reviewed 43 articles for data extraction. Results: Seventeen IAP are found in protected area, Nepal with the highest prevalence observed in Koshi Tappu Wildlife Reserve, followed by Chitwan and Sukhlaphanta National Park. The most problematic species in terrestrial ecosystems are Mikania micrantha, Lantana camara, and Chromolaena odorata. The grassland ecosystems of wildlife habitats, primarily in the Terai and Siwalik regions, are the most invaded. Various management approaches are employed to mitigate the spread and impact of IAP, including mechanical methods such as uprooting, burning, and cutting. However, these methods are costly, and context-specific interventions are needed. The study also explores the potential use of IAP for economic, ecological, or cultural purposes, such as medicinal properties, energy production potential, and economic viability. Local communities utilize these plants for animal bedding, mulching, green manure, briquette, and charcoal production. Conclusions: Applying silvicultural practices alongside mechanical management is recommended to maintain a healthy terrestrial ecosystem and utilize the removed biomass for valuable products, thereby reducing removal costs and increasing income sources, potentially benefitting both local communities and wildlife in protected areas.

• The Research Journal of the Costume Culture
• /
• v.32 no.3
• /
• pp.381-397
• /
• 2024

This study investigates the negative perceptions (veganphobia) held by consumers toward vegan diets and fashion and aims to foster a genuine acceptance of ethical veganism in consumption. The textual data web-crawled Korean online posts, including news articles, blogs, forums, and tweets, containing keywords such as "contradiction," "dilemma," "conflict," "issues," "vegan food" and "vegan fashion" from 2013 to 2021. Data analysis was conducted through text mining, network analysis, and clustering analysis using Python and NodeXL programs. The analysis revealed distinct negative perceptions regarding vegan food. Key issues included the perception of hypocrisy among vegetarians, associations with specific political leanings, conflicts between environmental and animal rights, and contradictions between views on companion animals and livestock. Regarding the vegan fashion industry, the eco-friendliness of material selection and design processes were seen as the pivotal factors shaping negative attitudes. Furthermore, the study identified a shared negative perception regarding vegan food and vegan fashion. This negativity was characterized by confusion and conflicts between animal and environmental rights, biased perceptions linked to specific political affiliations, perceived self-righteousness among vegetarians, and general discomfort toward them. These factors collectively contributed to a broader negative perception of vegan consumption. In conclusion, this study is significant in understanding the complex perceptions and attitudes that con- sumers hold toward vegan food and fashion. The insights gained from this research can aid in the design of more effective campaign strategies aimed at promoting vegan consumerism, ultimately contributing to a more widespread acceptance of ethical veganism in society.

• Tuberculosis and Respiratory Diseases
• /
• v.87 no.3
• /
• pp.234-251
• /
• 2024

Globally, providing evidence on the economic burden of chronic obstructive pulmonary disease (COPD) is becoming essential as it assists the health authorities to efficiently allocate resources. This study aimed to summarize the literature on economic burden evidence for COPD from 1990 to 2019. This study examined the economic burden of COPD through a systematic review of studies from 1990 to 2019. A search was done in online databases, including Web of Science, PubMed/Medline, Scopus, and the Cochrane Library. After screening 12,734 studies, 43 articles that met the inclusion criteria were identified. General study information and data on direct, indirect, and intangible costs were extracted and converted to 2018 international dollars (Int$). Findings revealed that the total direct costs ranged from Int$ 52.08 (India) to Int$ 13,776.33 (Canada) across 16 studies, with drug costs rannging from Int$ 70.07 (Vietnam) to Int$ 8,706.9 (China) in 11 studies. Eight studies explored indirect costs, while one highlighted caregivers' direct costs at approximately Int$ 1,207.8 (Greece). This study underscores the limited research on COPD caregivers' economic burdens, particularly in developing countries, emphasizing the importance of increased research support, particularly in high-resource settings. This study provides information about the demographics and economic burden of COPD from 1990 to 2019. More strategies to reduce the frequency of hospital admissions and acute care services should be implemented to improve the quality of COPD patients' lives and reduce the disease's rising economic burden.

• Korean Journal of Environment and Ecology
• /
• v.34 no.5
• /
• pp.396-401
• /
• 2020

As the world becomes more globalized, the non-native species issue has emerged as a problem that is growing internationally. In particular, the number of non-native turtles found in the wild has been increasing sharply in South Korea. At least 15 species of non-native turtles, including the red-eared slider (Trachemys scripta elegans) first imported in the 1970s, have been found in Korea. On October 15, 2019, an alligator snapping turtle (AST, Macrochelys temminckii) was found in a stream located in Gwangju city, South Korea. The discovery of AST became a big issue in South Korea as the animal is known for its large body size and aggressiveness and was featured widely in the mass media. In this study, to learn the public's perception of non-native species, we examined comments (opinions) to the online news articles about the AST. We collected 1,100 comments from the Internet news articles on the AST. Out of the 1,100 comments, 342 (31.1%) comments were related to non-native species' issues. Most of the respondents (97.7%, n=334) stated that the non-native species are a problem. Forty two comments mentioned potential threats posed by non-native species: non-native species' aggressive nature (n=11, 26.2%) and ecological disturbance (n=31, 73.8%). Lack of responsibility (n=122, 51.7%) was the major causative factor for the introduction of non-native species, and followed by indiscriminate pet trade (n=99, 42.0%), absence of relevant legislation (n=13, 5.5%), and absence of treatment (n=2, 0.8%). Animal registration (n=59, 45.7%) was the most commonly mentioned as the way to deal with the issue of the non-native species' invasion. Our results show that the public is aware of the seriousness of the invasion of non-native species, including AST. This study highlights that researchers and government officials need to consider the public's perception and opinions. We believe that our study can serve as an essential reference for the policy direction and the management of non-native species.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.1-23
• /
• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Science of Emotion and Sensibility
• /
• v.19 no.4
• /
• pp.13-20
• /
• 2016

Recently, life-logging service which has expanded to measure and record the daily life of the users and to share with others are increasing. In particular, as life-logging services based on the application has become popular with the development of wearable-devices and smart-phones, the contents of this service are produced by user behavior and are provided in infographic menu form. The purpose of this paper is to extract user behavior and classify for making contents items of life-logging service. For this paper, the first of all, we discuss the definition and characteristics of life-logging and research the contents based on user behavior related to life-logging by the publications including thesis, articles, and books. Secondly, we extract and classify the user behavior to build the contents for life-logging service. We gather users' action words from publication materials, researches, and contents of existing life-logging service. And then collected words are analyzed by FGI (Focus Group Interview) and survey. As the result, 39 words which suit for contents of life-logging service are extracted by verify suitability. Finally, the extracted 39 words are classified for 19 categories -'Eat', 'Keep house', 'Diet', 'Travel', 'Work out', 'Transit', 'Shoot', 'Meet', 'Feel', 'Talk', 'Care for', 'Drive', 'Listen', 'Go online', 'Sleep', 'Go', 'Work', 'Learn', 'Watch' - which are suggested by the surveys, statistical analysis, and FGI. We will discuss the role and limitations of this results to build contents configuration based on life-logging application in this study.

• The Journal of the Korea Contents Association
• /
• v.12 no.2
• /
• pp.40-51
• /
• 2012

Recently, many users discuss and argue with others using replying comments. This implies that a series of comments can be a new source of information since various opinions can be appeared in the dispute. It is important to understand the implicit dispute structure immanent in the comment set. In this paper, we examine the characteristics of disputes using replying comments in the Internet forum sites using a set of test articles with the comments collected from SketicalLeft and Agora, which are famous Internet forum sites in Korea. And we propose a new method for detecting and visualizing the dispute sections and relations from a large set of replying comments. To show the performance of our method, we measured precision, recall, and F-measure. According to the experimental results, the F-measures of the detection of the comments in dispute are about 0.84 (SketpcialLeft) and 0.83 (Agora); those of the detection of the commenter pairs in dispute are 0.75 (SketpcialLeft) and 0.82 (Agora), respectively. Since our method exploits the temporal order of commenters to detect the disputes, it is not dependent on the host language nor on the typos in comments. Also, our method can help the readers to grasp the structure of controversy hidden in the comment set through the visualized view.

• Journal of Digital Convergence
• /
• v.14 no.8
• /
• pp.19-36
• /
• 2016

The purpose of this study was to analyze domestic and overseas cases of flipped learning instructional design model and actual classes in K-12 Education, and find out educational implications in order to design effective flipped learning. Papers, 14 articles in domestic and international journals, were collected. As results of the analysis, first, flipped learning instructional model was presented as flipped learning that applied to ADDIE model and 8C model etc. Second, 'Activities before classroom' consisted of watching lecture videos, lecture notes etc. 'Activities during classroom' was checking prior learning in early stage, individual activities and cooperative activities in middle stage, and solving quizzes, reviewing in later stage. After class, students performed tasks and questions&answers. Third, in case of creating lecture video, they used application such as Screencast-o-matic, Explain Everything; In contrast, some cases utilized online web-sites such as YouTube or Phet. Fourth, positive results were shown in learners' academic achievement, motivation and learning attitude etc. This research has a significance in terms of analyzing the flipped learning instructional model and flipped learning activities, and providing the preliminary data to facilitate the design for the effective flipped learning.