• Asian Journal for Public Opinion Research
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• v.6 no.1
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• pp.31-38
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• 2018

Leading up to the 2019 presidential election in Indonesia, campaigns have emerged through social media, particularly Twitter, using various hashtags, such as #2019GantiPresiden (2019 Change President) and #TetapJokowi (Always Jokowi). This paper tries to understand the presidential candidates' power map in forming opinions and influencing voter behavior by analyzing Twitter from August 6, 2018 to September 15, 2018, just before the beginning of the official campaign period, by searching for the keyword "pemilihan presiden RI Tahun 2019" (RI presidential election in 2019). According to our NodeXL's analysis, there were 1,650 active Twitter users talking about the 2019 presidential election. The 1,650 Twitter users have formed a communication network of 46,750 relationships formed from messages in the form of tweets, comments, and retweets. Our analysis found that those mentioning "pilihan presiden 2019" form large communication networks around four clusters: one for each of the two candidates (Jokowi and Prabowo) and two for opinion leaders who are undecided about the election (Gus Mus and Mas Piyu). GusMus is a religious leader, as an official of the PBNU Rais Syuriah (an Islamic organization) and has a large following both on and off Twitter. "MasPiyu" is an unidentified Twitter user; he only has a large following on Twitter, but does not have support offline.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.3
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• pp.145-162
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• 2021

To identify key job duties and core competencies of data librarians, this study conducted content analyses of 75 U.S. job advertisements of data librarians and statistical analyses of 105 responses from incumbent data librarians. As a result, the key job duties identified are jobs related to collaboration, workshops, trainings, conferences, data service, research consultation, and research support. Core competencies identified are communication skills, teaching, diversity, inclusion, and equality, data management, and data tool. This study is significant in that it analyzed the key duties and core competencies of the data librarians using the most up-to-date data and opinions collected from incumbent people. It can be a basis for future study such as on job satisfaction, user satisfaction, and perception surveys for data librarians.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.145-153
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• 2020

Recently, keyword extraction from social big data has been widely used for the purpose of extracting opinions or complaints from the user's perspective. Regarding this, our previous work suggested a method to improve accuracy of keyword extraction based on the notion of cohesion scoring, but its accuracy can be degraded when the number of input reviews is relatively small. This paper presents a method to resolve this issue by applying simplified morphological analysis as a postprocessing step to extracted keywords generated from the algorithm discussed in the previous work. The proposed method enables to add analysis rules necessary to process input data incrementally whenever new data arrives, which leads to reduction of a dictionary size and improvement of analysis efficiency. In addition, an interactive rule adder is provided to minimize efforts to add new rules. To verify performance of the proposed method, experiments were conducted based on real social reviews collected from online, where the results showed that error ratio was reduced from 10% to 1% by applying our method and it took 450 milliseconds to process 5,000 reviews, which means that keyword extraction can be performed in a timely manner in the proposed method.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.141-150
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• 2021

With the recent spread of the concept of Smart Cities which is to solve urban problems with ICT technology, Living Lab, which identifies the demands of citizens who dwell in the city and verifies the acceptability of the services being introduced, has become an important topic. Living Lab is an open innovation platform introduced in consideration of the user's perspective in real life and is a new approach in that service developers use collective intelligence in the process of Co-creation with users. Living Lab is operated on topics which is close to citizens' daily lives such as energy, housing, transportation, and education. In particular, as energy and environmental-focused Living Lab emerges in accordance with the 'Korean New Deal Policy', interest and importance in the field are increasing. The paper derives the characteristics of water resource Living Lab through case analysis of several Living Lab practices. Water resource Living Lab in Daejeon and Chuncheon, which are located in Korea, and water resource Living Lab in Romania and Indonesia are covered in this paper as the reference. The paper finally analyzes the case of Sambang Water Living Lab in Gimhae, which is the city located in southern part of Korea. As a result of case analysis, the urban water resource Living Lab focuses on the raw water of urban water resource and should respond sensitively to the safety of citizens. And for the success of this urban water resource Living Lab, it is essential to ensure that citizens participating in the Living Lab clearly understand the concept of water resources, and citizens' opinions to be implemented as services.

• The Journal of Information Systems
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• v.32 no.3
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• pp.151-164
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• 2023

Purpose This study aims to analyze the current status of consumer awareness on Internet banks by conducting a full investigation and collecting user opinions presented on Google Play. After cateogorizing the current dissatisfaction, we would like to present not only the direction of the Internet bank service of but also the improvements of the platform. Design/methodology/approach Using opinion mining, subjectivity analysis, polarity analysis, and polarity information analysis of comments were conducted step by step to extract negative and positive keywords. The extracted keywords analyzed the weights of the frequently appearing positive and negative keywords using the TF-IDF model. Based on previous studies that negative information is more sensitive to positive information, we tried to confirm the connection, proximity, and mediation of negative keywords. Semantic Network Analysis (SNA) was used to visualize the connection relationship between the negative comment keywords of the three Internet banks. Findings Domestic Internet banks such as Kakao Bank, K-Bank, and Toss Bank have attracted a lot of attention even before they were established, and after establishment, they have secured a wide range of users through platforms that are completely different from existing banks. This study found out that the convenience of the app affects the opening and transaction of non-face-to-face accounts, which are characteristics of domestic Internet banks, which also affects the bank's business strategy. In addition, this study shows that the business characteristics of the company can be identified.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.3-16
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• 2017

With the development and proliferation of three-dimensional(3D) printers, consumers in modern society can now print products of what they want three-dimensionally at home. However, consumers themselves would have to produce digital design maps that are compatible with 3D printers and to set up the optimum printing quality and temperature, as well as to pay for maintenance and repair of 3D printers and to respond to any possible lawsuits related to intellectual property right about designs in order to make possible consumer-tailored manufacturing through 3D printing. However, in reality, since it is very difficult for consumers to respond to these issues, it is necessary to develop services that perform 3D printing on behalf of consumers in the desired direction. Motivated by this objective, this study investigated user experiences on Shapeways(www.shapeways.com), which is a global online 3D printing product and sales companies, from many viewpoints in order to obtain insight into 3D printing services and modes which were preferred by consumers. The study result showed that quantitative evaluations on usability, search process, price adequacy, re-visit intention, diversity of design, and satisfaction of design was scored low overall. Furthermore, this study acquired insight about consumer-tailored 3D printing services through constructive suggestions on multi-language support, openness of manufacturing process, simultaneous operation of online and offline sites, design-oriented consumer-tailored manufacturing service, services that ensure delivery safety and product durability, and surface finishing services. This study is expected to provide a wide range of opinions not only on 3D printing service platform development but also on related industry and research.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Korean Business Review
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• v.14
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• pp.31-44
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• 2001

The purpose of auditing is to express an auditor's opinion on the fair presentation of the financial position and business operations of companies according to the financial accounting standards, and to raise the reliability of the financial statements and to enable the user of the financial statements to make a proper judgement on the companies. There should be an audit risk in the audit of the financial statements in a modem sense because it is done by the sampling audit not by the detailed one. Audit risk is the risk that an auditor may unknowingly fail to modify appropriately the auditors' report on financial statements containing a material misstatement. The audit risk eventually hurt the reliability of the financial statements when the auditors set up different audit risks because it is determined by the auditor's professional judgement. Thus, there have been negative opinions on the Audit Risk Model suggested in the SAS No. 47 because it cannot explain the process of auditor's judgement and bring different results. In view of the results so far achieved, which influences the auditor's decision making, should be done by the Belief Function Mode Model in a position of raising the reliability of the financial statements and emphasizing the usefulness and effectiveness of the auditing.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.13-27
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• 2019

This study shows the changes in the space created by the planning and leisure activities of Hangang River Park, focusing on the Yeouido portion of the Hangang River Park, which has the most users and the greatest degree of planning. The relationship between planning, behavior, and space changes are explained based on Giddens's Structural Theory. As research material, Hangang River Park plans and satellite photos were interpreted and newspaper articles were used to identifying the space changes and their causes, and a model of the space changes was derived through the application of the theory. The flow of space change in the Yeouido portion of the Hangang River Park due to planning and leisure activities is as follows. In the 1970s, the first sports spaces are made due to need from residents near the riverside, but huge plans for the utilization of the entire space were not realized. In the 1980s, leisure spaces were planned and developed through a comprehensive plan. Various sports spaces were built, but the environment of the spaces became a slum. In the 1990s, various leisure activities were revitalized due to the revision of the legal system, regulations on the usage of space, and space maintenance, and from the late 1990s, ecological issues arose along the Hangang River. In the 2000s, there was an overall space improvement project directed by two comprehensive plans, and cultural and ecological issues appeared in the Hangang River Park plans. However, actual leisure spaces were developed along with the promotion of large-scale activities. Regarding the structuration theory, elements of interaction, modality, and structure are the aspects of space changes in the Yeouido portion Hangang River Park. As the flow of the space change, the proportions of the comprehensive plan and the individual plans were similar. The comprehensive plan was influenced by the change of public businesses and the proliferation of large-scale activities. Individual plans were influenced by the user's activities and opinions. However, both plans were influenced by the users and suppliers. The leisure space of the Hangang River Park can be viewed as a social space, in terms of the structuring as a theory due to the user repeatedly changing the use of the space. The purpos of this study is to investigate the changes in the Hangang River Park space through planning and leisure activities. Through this study, we can understand the characteristics of the Hangang River Park in planning the leisure activity space.