• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.548-557
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• 2021

The purpose of this study was to determine the statistical usefulness of using atypical text data collected from media that are easy to collect to overcoming limits of the existing data related to economic activities of disabled people. In addition, by performing semantic network analysis, major issues by period that could not be grasped by statistical analysis were also identified. As a result, semantic network analysis revealed that the initiative of the public sector, such as the central and local government bodies, was strongly shown. On the other hand, in the private purchase sector, it was also possible to confirm the consumption revitalization trend and changes in production activities in the recent issue of Covid-19. While the term "priority purchase" had a statistically significant relation with the other two terms "vocational rehabilitation" and "employment for the disabled". For the regression results, while the term "priority purchase" had a statistically significant association with the other two terms "vocational rehabilitation" and "employment for the disabled". Further, some statistical analyses reveal that keyword data taken from media channels can serve as an alternative indicator. Implications for issue detection in the field of welfare economy for the disabled is also discussed.

• Korean small business review
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• v.43 no.4
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• pp.27-57
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• 2021

How does authenticity influence the process that conducts a company's CSR Strategy? Authenticity, an internal/external alignment condition that an employee feels in relation to an organization, means the decision on how true and beneficial to employees through their experiences, such as thoughts and emotions. Also, it can be understood as a process of meaning formation between the organization's strategy to conduct CSR and the perception of employees conducting CSR. To prove the relation between authenticity and CSR clearly, we used various techniques like Text Mining, Topic Modeling and Semantic network analysis about O corporation's 657 review data, from 2015 to 2021. As a result of the analysis, we find out the special issues and types. The analysis shows that the issue concerning the 'external image' is the biggest characteristic of authenticity perception in other conditions. Furthermore, the types of authenticity perception evaluations are largely divided into acceptance and rejection, in detail, five categories. This study indicates that organizations should consider both external and internal conditions when establishing CSR strategies. In addition, it is necessary to be an interactive circular relationship between the organization and employee, collecting and reflecting employee's perceptions. Finally, this study proposes ways to overcome problems related to interaction.

• Journal of Korean Elementary Science Education
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• v.41 no.1
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• pp.30-43
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• 2022

In this study, elementary students' science communication competence was investigated based on the grammatical features expressed in their language-use in classroom discourse and science writings. The classes were designed to integrate the evidence-based reasoning framework and traditional learning cycle and were conducted on fifth graders in an elementary school. Eight elementary students' discourse data and writings were analyzed using lexico-grammatical resource analysis, which examined the discourse text's content and logical relations. The results revealed that the student language used in analyzing data, interpreting evidence, or constructing explanations did not precisely conform to the grammatical features in science language use. However, they provided examples of grammatical metaphors by nominalizing observed events in the classroom discourses and those of causal relations in their writings. Thus, elementary students can use science language grammatically from science language-use experiences through listening to a teacher's instructional discourses or recognizing the grammatical structures of science texts in workbooks. The opportunities in which elementary students experience the language-use model in science learning need to be offered to understand the appropriate language use in the epistemic context of evidence-based reasoning and learn literacy skills in science.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.307-319
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• 2023

This study aims to explain the key concepts and principles of text-based generative artificial intelligence (AI) that has been receiving increasing interest and utilization, focusing on its application in science education. It also highlights the potential and limitations of utilizing generative AI in science education, providing insights for its implementation and research aspects. Recent advancements in generative AI, predominantly based on transformer models consisting of encoders and decoders, have shown remarkable progress through optimization of reinforcement learning and reward models using human feedback, as well as understanding context. Particularly, it can perform various functions such as writing, summarizing, keyword extraction, evaluation, and feedback based on the ability to understand various user questions and intents. It also offers practical utility in diagnosing learners and structuring educational content based on provided examples by educators. However, it is necessary to examine the concerns regarding the limitations of generative AI, including the potential for conveying inaccurate facts or knowledge, bias resulting from overconfidence, and uncertainties regarding its impact on user attitudes or emotions. Moreover, the responses provided by generative AI are probabilistic based on response data from many individuals, which raises concerns about limiting insightful and innovative thinking that may offer different perspectives or ideas. In light of these considerations, this study provides practical suggestions for the positive utilization of AI in science education.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Journal of Practical Agriculture & Fisheries Research
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• v.21 no.2
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• pp.103-114
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• 2019

In this study we examined the preferences of college life factors for students at Korea National College of Agriculture and Fisheries(KNCAF). Analytical techniques of unstructured data used opinion mining and text mining techniques, and the results of text mining were visualized as word cloud. And those results were used for statistical analysis of the students' willingness to farm after graduation. The items of the favorable survey consisted of 10 items in 5 areas including university image, self-capacity, dormitory, education system, and future vision. After classifying the emotions of positive and negative in the collected questionnaire, a dictionary of positive and negative was created to evaluate the preference. The items of 'college image' at the time of university support, 'self after 10 years' after graduation, 'self-capacity' and 'present KNCAF' showed high positive emotion. On the other hand, positive emotion was low in the items of 'college dormitory', 'educational course', 'long-term field practice' and 'future of Korean agriculture'. In the cross-analysis of the difference in the will to farming according to gender, farming base, and entrance motivation, the will to farm according to gender and entrance motivation showed statistically significant results, but it was not significant in farming base. Also in binary logistic regression analysis on the will to farming, the statistically significant variable was found to be 'motivation for admission'

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.347-373
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• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.1
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• pp.34-45
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• 2024

Companion animals are increasingly being recognized as members of society in outdoor public spaces. However, the presence of dogs in cities has become a subject of conflict between pet owners and non-pet owners, causing problems in terms of hygiene and noise. This study was conducted to analyze public complaint data using the keywords 'dog,' 'pet,' and 'puppy' through text mining techniques to identify the causes of conflicts in outdoor public spaces related to dogs and to identify key issues. The main findings of the study are as follows. First, the majority of dog-related complaints were related to the use of outdoor public spaces. Second, different types of outdoor public spaces have different spatial issues. Third, there were a total of four topics of dog-related complaints: 'Requesting a dog playground', 'Raising safety issues related to animals', 'Using facilities other than dog-only areas', and 'Requesting increased park management and enforcement related to pet tickets'. This study analyzed the perceptions of citizens surrounding pets at a time when the creation and use of public spaces related to pets are expanding. In particular, it is significant in that it applied a new method of collecting public opinions by adopting complaint data that clearly presents problems and requests.

• Information Systems Review
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• v.25 no.1
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• pp.233-255
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• 2023

The development of information technology(IT) has brought so-called "online experience" to satisfy our daily needs. The market for online experiences grew more during the COVID-19 pandemic. Therefore, this study attempted to analyze how the features of online experience services affect customer satisfaction by crawling structured and unstructured data from the online experience web site newly launched by Airbnb after COVID-19. As a result of the analysis, it was found that the structured data generated by service users on a C2C online sharing platform had a positive effect on the satisfaction of other users. In addition, unstructured text data such as experience introductions and host introductions generated by service providers turned out to have different subjectivity scores depending on the purpose of its text. It was confirmed that the subjective host introduction and the objective experience introduction affect customer satisfaction positively. The results of this study are to provide various implications to stakeholders of the online sharing economy platform and researchers interested in online experience knowledge management.

• The Korean Journal of Archival Studies
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• no.82
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• pp.47-86
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• 2024

The role of the archive providing the service is crucial for making records more widely known and utilized. The personal letters exchanged between Moon Ik-hwan and Park Yong-gil are unique personal records that fill the gaps left by public records during the politically tumultuous period of the early 1980s in Korea. This paper aims to shed light on the context of record management by comprehensively analyzing these letters in terms of their interrelationships. To achieve this, the study analyzes the context of 694 letters exchanged between the two during Moon Ik-hwan's imprisonment in the third prison following the Kim Dae-jung Conspiracy Case. The research methodology involved reviewing literature and records to summarize the historical context and personal backgrounds, and a comparative analysis was conducted to reveal the interrelationships and meanings within the texts of the letters. The findings of this study can be summarized into three key points. First, the paper outlines the shared context of the letters by summarizing the political and social circumstances of the time, particularly focusing on the Kim Dae-jung Conspiracy Case, and the characteristics of individual relationships. Second, it distinguishes the direct methods of letter exchange, categorizing them into routine and atypical methods, and identifies the relationships between the letters, the flow of dialogue within them, and their distinctive features. Third, it explores the interrelations and meanings between the contents of the letters. Through this analysis, it was confirmed that the two sets of letters, as a unified and expansive text, display characteristics of integration, competition, and expansion in their content. This analysis emphasizes the importance of understanding the context of letters in record management and demonstrates the need for archives to provide rich contextual information when offering access to letters.