In order to help the understanding of web novel users, this study was intended to quantitatively verify the user's behavioral types according to the characteristics of web novels. For this purpose, the direction of the study proceeded as follows. First, the motives of web novel users were investigated by referring to the motives of other digital content users. In addition, specific behavioral types of users were also collected. As a result, the motivation for using web novels was found to be 'interpersonal relationships and information acquisition with others', 'leisure activities', and 'escape from reality/relieve tension'. After that, the groups were classified as to whether there was a difference between groups according to the motives of use. As a result, the 'hobbies' type, a group with a particularly high motivation for using leisure activities, the 'stress relief' type, a group with very high escapism and tension relief characteristics, and a group with high interpersonal relationships and information acquisition with others The 'communication' type was classified as a 'multipurpose' type with high overall motivation characteristics. Then, in order to find out the specific characteristics between the types, personas were constructed based on the different behavior type data. Through this, the theoretical contribution of this study is meaningful in that it revealed the motives of web novel users. As a practical contribution, the persona was formed by combining the users' motives and behavioral patterns and visualized to be close to the actual representative users. These results are expected to help improve the web novel service by providing useful indicators for actual writers, platform managers, and users.
Journal of the Korean BIBLIA Society for library and Information Science
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v.33
no.1
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pp.371-401
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2022
If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.
Han, Sang Kyu;Kim, Yoo Jung;An, A Ju;Heo, Eun Young;Kim, Jeong Whun;Lee, Joong Seek
Design Convergence Study
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v.16
no.6
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pp.123-135
/
2017
In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.
Ju-eun Kim;Seung-hee Seo;Beong-jin Seok;Heoyn-su Byun;Chang-hoon Lee
Journal of the Korea Institute of Information Security & Cryptology
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v.33
no.3
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pp.471-485
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2023
Recently, due to the nature of blockchain that guarantees users' anonymity, more and more cases are being exploited for crimes such as illegal transactions. However, cryptocurrency is protected in cryptocurrency wallets, making it difficult to recover criminal funds. Therefore, this study acquires artifacts from the data and memory area of a local PC based on user behavior from four browser extension wallets (Metamask, Binance, Phantom, and Kaikas) to track and retrieve cryptocurrencies used in crime, and analyzes how to use them from a digital forensics perspective. As a result of the analysis, the type of wallet and cryptocurrency used by the suspect was confirmed through the API name obtained from the browser's cache data, and the URL and wallet address used for the remittance transaction were obtained. We also identified Client IDs that could identify devices used in cookie data, and confirmed that mnemonic code could be obtained from memory. Additionally, we propose an algorithm to measure the persistence of obtainable mnemonic code and automate acquisition.
The traditional retail industry significantly changed over the past decade due to the mobile and online technologies. This change has been accompanied by a shift in consumer behavior regarding purchasing patterns. Despite the rise of online shopping, there are still specific categories of products, such as "Processed food" in Mongolia, for which traditional shopping remains the preferred purchase method. To prepare for the inevitable future of retail businesses, firms need to closely analyze the performance of their offline stores to plan their further actions in a new multi-channel environment. Retailers must integrate diverse channels into their operations to stay relevant and adjust to the shifting market. In this research, we have analyzed the performance data such as sales, profit, and amount of sales of offline stores by using clustering approach. From the clustering, we have found the several distinct insights by comparing the circumstances and performance of retail stores. For the certain retail stores, we have proposed three different strategies: a fulfillment hub store between online and offline channels, an experience store to elongate customers' time on the premises, and a merge between two non-related channels that could complement each other to increase traffic based on the store characteristics. With the proposed strategies, it may enhance the user experience and profit at the same time.
The concept of Mydata emerged with the expansion of the data economy. MyData aims to empower individuals by enhancing their right to self-determination over their personal data. The use of MyData is expected to enable the provision of innovative service in various fields. Since 2022, MyData has been introduced and actively used in the financial sector. In the future, not only financial institutions but also Bigtech and Fintech companies are expected to actively join and demonstrate rapid expansion. To ensure steady growth for MyData in the financial sector, it is necessary to assess acceptance behaviors from multiple perspectives. However, the majority of existing research solely focuses on positive acceptance. This study analyzed the impact of users' personal characteristics and innovation characteristics on both innovation resistance and acceptance resistance. The analysis revealed that personal and innovation characteristics contribute to an increase in distrust and innovation resistance in the MyData service. In addition, it has been confirmed that it can lead to actions such as delayed acceptance and refusal to accept. The results of this study offer both theoretical and practical insights into user behavior within the MyData service market.
Yeeun Kim;Junga Kim;Siyun Chae;Jiwon Hong;Seongmin Kim
Journal of the Korea Institute of Information Security & Cryptology
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v.34
no.2
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pp.263-279
/
2024
With the increasing trend of Cloud migration, security threats in the Cloud computing environment have also experienced a significant increase. Consequently, the importance of efficient incident investigation through log data analysis is being emphasized. In Cloud environments, the diversity of services and ease of resource creation generate a large volume of log data. Difficulties remain in determining which events to investigate when an incident occurs, and examining all the extensive log data requires considerable time and effort. Therefore, a systematic approach for efficient data investigation is necessary. CloudTrail, the Amazon Web Services(AWS) logging service, collects logs of all API call events occurring in an account. However, CloudTrail lacks insights into which logs to analyze in the event of an incident. This paper proposes an automated analysis framework that integrates Cloud Matrix and event information for efficient incident investigation. The framework enables simultaneous examination of user behavior log events, event frequency, and attack information. We believe the proposed framework contributes to Cloud incident investigations by efficiently identifying critical events based on the ATT&CK Framework.
This study examines the factors contributing to waterfront satisfaction among different generations, utilizing a survey on the use and perception of waterfront areas by residents of apartment houses in Tokyo's coastal region. The variables used in this study are developed through a review of existing literature, focusing on factors related to waterfront usage. Specifically, we select the proximity to the waterfront, duration of stay at the waterfront, and frequency of visits to the waterfront as key variables for investigation. In addition, the study further incorporates aspects related to waterfront recognition, such as the space, user behavior, and management status of the waterfront. Utilizing these variables, we carry out a correlation analysis to investigate the association between generational use and perception of the waterfront and their satisfaction with water-related experiences. The results identify three key factors to enhance waterfront satisfaction: First, to increase visits from both younger and older generations, improving pedestrian access to the waterfront is essential. Second, for middle-aged and older generations, creating waterfront areas closer to their residences can reduce travel distance and time, encouraging more frequent use. Third, maintaining clean and well-kept waterfront spaces is fundamental for all generations to enjoy relaxing experiences, thereby improving overall satisfaction.
Current analysis of air passengers mainly relies on statistical methods, but there are limitations in analyzing detailed aspects such as travel routes, number of regional passengers and airport access times. However, with the advancement of big data technology and revised three data acts, big data-based transportation analysis has become more active. Mobile communication data, which can precisely track the location of mobile phone terminals, can serve as valuable analytical data for transportation analysis. In this paper, we propose a air passenger Origin/Destination (O/D) extraction algorithm based on mobile communication data that overcomes the limitations of existing air transportation user analysis methods. The algorithm involves setting airport signal detection zones at each airport and extracting air passenger based on their base station connection history within these zones. By analyzing the base station connection data along the passenger's origin-destination paths, we estimate the entire travel route. For this paper, we extracted O/D information for both domestic and international air passengers at all domestic airports from January 2019 to December 2020. To compensate for errors caused by mobile communication service provider market shares, we applied a adjustment to correct the travel volume at a nationwide citizen level. Furthermore correlation analysis was performed on O/D data and aviation statistics data for air traffic users based on mobile communication data to verify the extracted data. Through this, there is a difference in the total amount (4.1 for domestic and 4.6 for international), but the correlation is high at 0.99, which is judged to be useful. The proposed algorithm in this paper enables a comprehensive and detailed analysis of air transportation users' travel behavior, regional/age group ratios, and can be utilized in various fields such as formulating airport-related policies and conducting regional market analysis.
According to technology acceptance model(TAN) which is one of the most important research models for explaining IT users' behavior, on intention of using IT is determined by usefulness and ease of use of it. However, TAM wouldn't explain the performance of using IT while it has been considered as a very good model for prediction of the intention. Many people would not be confirmed in the performance of using IT until they can control it at their will, although they think it useful and easy to use. In other words, in addition to usefulness and ease of use as in TAM, controllability is also should be a factor to determine acceptance of IT. Especially, there is a very close relationship between controllability and ease of use, both of which explain the other sides of control over the performance of using IT, so called perceived behavioral control(PBC) in social psychology. The objective of this study is to identify the relationship between ease of use and controllability, and analyse the effects of both two beliefs over performance and intention in using IT. For this purpose, we review the issues related with PBC in information systems studies as well as social psychology, Based on a review of PBC, we suggest a research model which includes the relationship between control and performance in using IT, and prove its validity empirically. Since it was introduced as qa variable for explaining volitional control for actions in theory of planned behavior(TPB), there have been confusion about concept of PBC in spite of its important role in predicting so many kinds of actions. Some studies define PBC as self-efficacy that means actor's perception of difficulty or ease of actions, while others as controllability. However, this confusion dose not imply conceptual contradiction but a double-faced feature of PBC since the performance of actions is related with both self-efficacy and controllability. In other words, these two concepts are discriminated and correlated with each other. Therefore, PBC should be considered as a composite concept consisting of self-efficacy and controllability, Use of IT has been also one of important areas for predictions by PBC. Most of them have been studied by analysis of comparison in prediction power between TAM and TPB or modification of TAM by inclusion of PBC as another belief as like usefulness and ease of use. Interestingly, unlike the other applications in social psychology, it is hard to find such confusion in the concept of PBC in the studies for use of IT. In most of studies, controllability is adapted as PBC since the concept of self-efficacy is included in ease of use explicitly. Based on these discussions, we can suggest perceived use control(PUC) which is defined as perception of control over the performance of using IT and composed of controllability and ease of use as sub-concepts. We suggest a research model explaining acceptance of IT which includes the relationships of PUC with attitude and performance of using IT. For empirical test of our research model, two user groups are selected for surveying questionnaires. In the first group, there are freshmen who take a basic course for Microsoft Excel, and the second group consists of senior students who take a course for analysis of management information by Excel. Most of measurements are adapted ones that have been validated in the other studies, while performance is real score of mid-term in each class. In result, four hypotheses related with PUC are supported statistically with very low significance level. Main contribution of this study is suggestion of PUC through theoretical review of PBC. Specifically, a hierarchical model of PUC are derived from very rigorous studies in the relationship between self-efficacy and controllability with a view of PBC in social psychology. The relationship between PUC and performance is another main contribution.
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