• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of Navigation and Port Research
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• v.47 no.1
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• pp.1-9
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• 2023

Many studies have analyzed marine accidents, and since marine accident information is updated every year, it is necessary to periodically analyze and identify the causes. The purpose of this study was to prevent accidents by identifying and analyzing the causes of marine accidents using previous and new data. In marine accident data, 1,921 decisions by the Korea Maritime Safety Tribunal on marine accidents on fishing ships over 16 years were collected in consideration of the specificity of fishing ships, and 1,917 cases of accident notification text history by the Ministry of Maritime Affairs and Fisheries over 3 years were collected. The decision data and text data were classified according to variables and quantified. Prior probability was calculated using a Bayesian network using the quantified data, and fishing ship marine accidents were predicted using backward propagation. Among the two collected datasets, the decision data did not provide the types of fishing ships and fishing areas, and because not all fishing ship accidents were included in the decision data, the text data were selected. The probability of a fishing ship marine accident in which engine damage would occur in the West Sea was 0.0000031%, as calculated by backward propagation. The expected effect of this study is that it is possible to analyze marine accidents suitable for the characteristics of actual fishing ships using new accident notification text data to analyze fishing ship marine accidents. In the future, we plan to conduct research on the causal relationship between variables that affect fishing ship marine accidents.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Korean Journal of Social Welfare
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• v.65 no.4
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• pp.165-193
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• 2013

This study purposes to explore the growing process through spousal bereavement in later life, and to develop the theory. A qualitative research was conducted, and the participants were 17 seniors. The analysis according to Strauss and Corbin's grounded theory(1998), resulted in 143 concepts, 43 subcategories, and 19 categories. Range analysis according to paradigm showed that the causal conditions were 'marital relationships', 'independent/dependent tendencies', and 'emotional readiness for the death of a spouse', and the phenomena were 'depression', 'hopelessness', 'daily stress', 'psychological intimidation', 'regret', and 'sense of being freed'. The contextual conditions that affect these phenomena were 'desire for intimate personal relationships' and 'desire to maintain independence'; the action/interaction strategies to manage the phenomena were 'facing reality' and 'efforts for construction of the new life'; and the mediating conditions that promote or suppress these action/interaction strategies were 'social support' and 'spirituality'. The results were 'reconstruction of the meaning in life', 'increase in self-esteem', 'reinforcement of social network' and 'embrace and acceptance'. Furthermore, when personal growth after bereavement of a spouse was analyzed focusing on changes over time, the growth process consisted of three steps: 'sadness and despair', 'embracing and moving forward', and 'personal growth'. The pattern analyses were performed to typify recurring relations by category, and 5 types were derived. The results of our study show that personal growth after spousal loss is an integrative process in life after crisis, and can be conceptualized as the process of overcoming the despair that immediately follows the death of a spouse, seeking a new life by actively taking control, and discovering a strengthened self.

• Asia pacific journal of information systems
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• v.24 no.1
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• pp.93-112
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• 2014

As personal data breach reared up as a problem domestically and globally, organizations appointing chief privacy officers (CPOs) are increasing. Related Korean laws, 'Personal Data Protection Act' and 'the Act on Promotion of Information and Communication Network Utilization and Information Protection, etc.' require personal data processing organizations to appoint CPOs. Research on the characteristics and role of CPO is called for because of the importance of CPO being emphasized. There are many researches on top management's role and their impact on organizational performance using the Upper Echelon theory. This study investigates what influence the characteristics of CPO gives on the organizational privacy performance. CPO's definition varies depending on industry, organization size, required responsibility and power. This study defines CPO as 'a person who takes responsibility for all the duties on handling the organization's privacy,' This research assumes that CPO characteristics such as role, personality and background knowledge have an influence on the organizational privacy performance. This study applies the part relevant to the upper echelon's characteristics and performance of the executives (CEOs, CIOs etc.) for CPO. First, following Mintzberg and other managerial role classification, information, strategic, and diplomacy roles are defined as the role of CPO. Second, the "Big Five" taxonomy on individual's personality was suggested in 1990. Among these five personalities, extraversion and conscientiousness are drawn as the personality characteristics of CPO. Third, advance study suggests complex knowledge of technology, law and business is necessary for CPO. Technical, legal, and business background knowledge are drawn as the background knowledge of CPO. To test this model empirically, 120 samples of data collected from CPOs of domestic organizations are used. Factor analysis is carried out and convergent validity and discriminant validity were verified using SPSS and Smart PLS, and the causal relationships between the CPO's role, personality, background knowledge and the organizational privacy performance are analyzed as well. The result of the analysis shows that CPO's diplomacy role and strategic role have significant impacts on organizational privacy performance. This reveals that CPO's active communication with other organizations is needed. Differentiated privacy policy or strategy of organizations is also important. Legal background knowledge and technical background knowledge were also found to be significant determinants to organizational privacy performance. In addition, CPOs conscientiousness has a positive impact on organizational privacy performance. The practical implication of this study is as follows: First, the research can be a yardstick for judgment when companies select CPOs and vest authority in them. Second, not only companies but also CPOs can judge what ability they should concentrate on for development of their career relevant to their job through results of this research. Cultural social value, citizen's consensus on the right to privacy, expected CPO's role will change in process of time. In future study, long-term time-series analysis based research can reveal these changes and can also offer practical implications for government and private organization's policy making on information privacy.

• Nutrition Research and Practice
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• v.8 no.4
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• pp.368-376
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• 2014

BACKGROUND/OBJECTIVES: The objectives of this study were to investigate the effects of lycopene on the migration, adhesion, tube formation capacity, and p38 mitogen-activated protein kinase (p38 MAPK) activity of endothelial progenitor cells (EPCs) cultivated with high glucose (HG) and as well as explore the mechanism behind the protective effects of lycopene on peripheral blood EPCs. MATERIALS/METHODS: Mononuclear cells were isolated from human peripheral blood by Ficoll density gradient centrifugation. EPCs were identified after induction of cellular differentiation. Third generation EPCs were incubated with HG (33 mmol/L) or 10, 30, and $50{\mu}g/mL$ of lycopene plus HG. MTT assay and flow cytometry were performed to assess proliferation and apoptosis of EPCs. EPC migration was assessed by MTT assay with a modified boyden chamber. Adhesion assay was performed by replating EPCs on fibronectin-coated dishes, after which adherent cells were counted. In vitro vasculogenesis activity was assayed by Madrigal network formation assay. Western blotting was performed to analyze protein expression of both phosphorylated and non-phosphorylated p38 MAPK. RESULTS: The proliferation, migration, adhesion, and in vitro vasculogenesis capacity of EPCs treated with 10, 30, and $50{\mu}g/mL$ of lycopene plus HG were all significantly higher comapred to the HG group (P < 0.05). Rates of apoptosis were also significantly lower than that of the HG group. Moreover, lycopene blocked phosphorylation of p38 MAPK in EPCs (P < 0.05). To confirm the causal relationship between MAPK inhibition and the protective effects of lycopene against HG-induced cellular injury, we treated cells with SB203580, a phosphorylation inhibitor. The inhibitor significantly inhibited HG-induced EPC injury. CONCLUSIONS: Lycopene promotes proliferation, migration, adhesion, and in vitro vasculogenesis capacity as well as reduces apoptosis of EPCs. Further, the underlying molecular mechanism of the protective effects of lycopene against HG-induced EPC injury may involve the p38 MAPK signal transduction pathway. Specifically, lycopene was shown to inhibit HG-induced EPC injury by inhibiting p38 MAPKs.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.79-95
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• 2017

This Study Investigates Whether R&D Capabilities and Market Orientation have Significant Effects on Product Innovation Performance in Order to Enhance Customer Value and Technology Innovation Competitiveness Considering the Characteristics of Rapidly Changing Semiconductor Industry. In other Words, as in the Research Model, the Purpose of this Study is to Investigate the Causal Relationship between the Independent Variable, R&D Capability and Market Orientation, on Product Innovation Performance, which is a Dependent Variable, through the Moderating Variable of Technological Innovation Orientation. For this Study, we Conducted a Questionnaire Survey on the Employees of Development Companies in the Semiconductor Industry and Finally Collected 118 Valid Questionnaires. The Collected Data was Analyzed by Multiple Regression Analysis with Demographic Characteristics as Control Variable and Hierarchical Regression Analysis was Conducted with the Moderating Effects of Technological Innovation Orientation. The Results Showed that the Higher the R&D Intensity and the External Network Capacity, the Higher the Product Innovation Performance. Also, the Product Innovation Performance was Higher than the Customer Orientation and Competitor Orientation Among the Market Orientation. In Addition, only R&D Capability Confirms that Technology Innovation Orientation is Moderated. The Result of this Study is to Improve Understanding of R&D Capability and Market Orientation in Creating of Product Innovation Performance of Semiconductor Companies and to offer Valuable Research Data in Empirically Supporting that Technological Innovation Orientation is an Important Moderating Factor in Creating Firm's Product Innovation Performance and Sustainable Competitive Advantage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.594-603
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• 2019

This purpose of this study is for an Airline company to discover and utilize new knowledge because knowledge and information are considered core tools for achieving high performance and competitive advantage, and achieving high performance and competitive advantage will surely determine the long-term survival of airline companies. Therefore, this study aims to reveal the causal relationships among different types of organizational culture, the knowledge sharing activities and the effectiveness of organizational work by airline members from a holistic viewpoint. The results of analysis are as follows. First, when examining the effects of the organizational culture types of airline members on knowledge sharing, a creative innovation culture, a relational group culture and a hierarchical orientation culture all showed positive effects on knowledge sharing. Second, the knowledge sharing by airline members showed a significant positive effect on the effectiveness of organizational work. Third, the creative innovation culture, the relational group culture and the hierarchical orientation culture all showed positive effects on the effectiveness of organizational work. Fourth, knowledge sharing did not have a mediating effect on the relationship between organizational culture and the effectiveness of organizational work.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.222-230
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• 2022

Recently, Korea's cultural content industry is developing, and behind the growing recognition around the world is the real-time sharing service of global network users due to the development of science and technology. In particular, in the case of YouTube, its propagation power is fast and powerful in that everyone, not limited users, can become potential video providers. As more than 80% of mobile phone users are using YouTube in Korea, YouTube's information means that psychological factors of users are reflected. For example, information such as the number of video views, likes, and comments of a channel with a specific personality shows a measure of the channel's personality interest. This is highly related to the fact that information such as the frequency of keyword search on portal sites is closely related to the stock market economically and psychologically. Therefore, in this study, YouTube information from a representative entertainment company is collected through a crawling algorithm and analyzed for the causal relationship with major variables related to stock prices. This study is considered meaningful in that it conducted research by combining cultural content, IT, and financial fields in accordance with the era of the fourth industry.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.383-393
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• 2023

We attempted to provide a way to improve job satisfaction by analyzing the relationship between the factors influencing job satisfaction directly or indirectly by the ecological system factors of long-term care worker who provide elderly care services at home benefit institutions. In this study, job satisfaction was confirmed to have a positive (+) correlation with all ecological factors except for social and cultural environmental factors by setting the causal relationship between the social and social characteristics of long-term care worker and job satisfaction as dependent variables. The factors with the highest correlation with job satisfaction were social support, followed by family support, job conditions, trust in welfare policies for the elderly, self-efficacy, and self-esteem. Therefore, it can be seen that nursing care workers who recognize positive support from the surrounding social network and family surrounding nursing care workers and positively recognize job conditions are generally positive.