• Journal of Information Technology Services
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• v.23 no.2
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• pp.1-12
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• 2024

This study aims to find ways to increase the declining donation intention by using machine learning techniques. To this end, in order to predict factors that affect donations between the MZ generation and the senior generation, various machine learning algorithms, including logistic regression analysis, are applied to build a model to determine variables that affect donation intention, and provide statistical verification and evaluation indicators. In this study, differences in donation intention by generation were expected as a variable affecting donation intention, and the senior generation was expected to show a higher donation intention tendency than the younger generation. However, although the research results were not statistically significant, the younger generation showed a higher intention to donate, and these results are interpreted to mean that value consumption and ethical consumption, which are important to today's MZ generation, also influenced donations. However, there were differences between generations in the amount of donations, and higher donation amounts were confirmed among the senior generation (those in their 50s or older) than the younger generation. In addition, the results of the logistic regression analysis showed that previous donation experience had a positive effect on future donation intention, and the more motivation and importance of donation and various social participation activities online and offline, the more active one became in donating.

• The Journal of Korean Institute for Practical Engineering Education
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• v.5 no.1
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• pp.52-57
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• 2013

Because of rapid spread of the PC, many users have been enjoying a variety of content as PC. Especially in recent years, young people has increased dramatically PC usage. Young people get more easily information using a PC. Especially they relieve their stress through online games and feel another fun of virtual reality. It is obviously a good effect that they contact IT culture with rapidly developed. But young people's perspective with world is narrow because of doing more indoor activities than outdoor. Therefore we built Spot experience voucher system using smart phone application. We hope that many young people act outdoor activities. And Our product offer hybrid device by developing HTML5-based app. Thus this app will give interest of spot-experience to young-people. So If young people use this app, they can have many experience and see diverse aspects.

• Journal of Internet Computing and Services
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• v.13 no.6
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• pp.17-24
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• 2012

The purpose of this study is to test the effect of personal communication activities using smart phone instant messenger during normal office hours on job performance in the workplace. To do this, empirical data were collected by conducting a field survey of smart phone users, and structural equation model was used for the purpose of analyzing the data acquired by the survey. A structural equation model was designed and constructed by such factors like personal instant messaging with the outside friends and co-workers on job performance. In addition, task characteristics set as a moderating effect between personal instant messaging with the outside friends/co-workers and job performance. The results of the analysis are summarized as follows; First, personal instant messaging with the outside friends generally has a negative effect on job performance, in addition in high task interdependence area the former has more effect on the latter. Second, personal instant messaging with co-workers has a positive effect on job performance.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.92-99
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• 2022

This study show the empirical results and the models that explain the content creator's personal brand value in the user-generated content platform. Producer's brand value performance could have enhancement and dilution by their activities for the long-term and repetitive change. Therefore, for the measure and analysis, the models have to catch the effect from producer's the diverse activities. This study would find the guideline by competitive analysis between (1) the impact of in-group user's self-motivated participation and (2) the impact of the social links from the outside platform. Based on the analysis results, producer's creation activity as focused on the specific and professional category increase their brand value for the long-term. However, producers would have to upload diverse category, after users are bored to their similar videos' as before. These empirical results would be a guidelines to the content management strategies for producers and the platform.

• The Journal of Industrial Distribution & Business
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• v.11 no.2
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• pp.49-59
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• 2020

Purpose: Online and social media and mobile shopping are increasing and companies are required to provide personal information in order to supplement the non-invasive characteristics of the channels. With the increased provision of personal information, consumers' personal and social concerns about the prevention of personal information infringement are also increasing, and in response, personal or opt-in marketing has emerged to compensate for reckless information abuse. Despite the background of this emergence, the existing prior studies are limited to ignoring the negative feelings of consumers in the real world, including only the net function and positive effect of the opt-in mail. Research design, data and methodology: The research framework was intended to utilize the impact of human marketing activities on consumer attitudes combined with positive and negative factors. Factors that positively affect attitudes toward permation marketing were presented, such as informality, and perceived risks were presented as negative impact factors. Also, based on previous prior research, the prior factors of opt-in marketing were to present the effect on purchase intent through the medium of attitude toward opt-in marketing. Results: In this study, we used the framework of a two factor theory to address positive and negative factors as a leading factor in the customer attitude toward opt-in mail advertising, and as a result, functionality and personalization have a positive effect on customer attitude and perceived risk have a negative impact on customer attitude. In addition, it was confirmed that the customer attitude formed this way affects the intention to purchase again. Conclusions: This study suggests that we have demonstrated that marketing, an opt-in marketing that has been recognized as part of marketing that is deployed after obtaining customer consent, has been applied without any other marketing methodology. E-mail advertising at this point also provides practical implications that the system safeguards are in place under an opt-in protocol or system, and that even if an e-mail advertisement is carried out, customers will need to look at the level of awareness about the risks, and suggests that they need to consider the customer's journey that could lead to purchase at the content level.

• Journal of Digital Contents Society
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• v.9 no.3
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• pp.491-498
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• 2008

The leakage of sensitive information by an insider within the organization becomes a serious threat nowadays. Sometimes, these insider threats are more harmful to an organization than external attack. Companies cannot afford to continue ignoring the potential of insider attacks. The purpose of this study is to design an integrated log analysis system that can detect various types of information leakages. The system uses threat rules generated through risk analysis, and monitors every aspect of the online activities of authorized insider. Not only should system have the ability to identify abnormal behavior, they should also be able to predict and even help to prevent potential risk. The system is composed of three modules, which are log collector, log analyzer and report generator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.69-74
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• 2021

Internet access is also increasing as online activities increase due to the influence of Corona 19. However, network attacks are also diversifying by malicious users, and DDoS among the attacks are increasing year by year. These attacks are detected by intrusion detection systems and can be prevented at an early stage. Various data sets are used to verify intrusion detection algorithms, but in this paper, CICIDS2017, the latest traffic, is used. DDoS attack traffic was analyzed using the decision tree. In this paper, we analyzed the traffic by using the decision tree. Through the analysis, a decisive feature was found, and the accuracy of the decisive feature was confirmed by proceeding the decision tree to prove the accuracy of detection. And the contents of false positive and false negative traffic were analyzed. As a result, learning the feature and the two features showed that the accuracy was 98% and 99.8% respectively.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3777-3785
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• 2013

This study aimed to find out adolescents' media literacy in terms of reading, writing, and enjoying media or messages. For the purpose, we analyzed the data garnered from 1,036 students enrolled in 5 middle and 5 high schools, respectively. The analyses of the data are summarized as follows: First, mobile phone was most widely used among others, followed by TV, the Internet, mp3 player, computer or video game, radio, a video or DVD in the order. Second, a gender effect was significant in terms of the variety of activities with the Internet, mobile, and SNS: boys were more active in the use of the Internet while girls carried out more activities with a mobile phone and SNS media. Third, high school students showed more critical attitude towards information on the Website than did the middle school students. Fourth, Girls than boys, and high schoolers than middle schoolers, tended to be more active in the production of contents, self-expression, as well as participating in social and political issues online. Fifth, for the enjoyment experiences, time spent for games took up the most of the students' leisure activities, followed by watching TV and the use of the Internet. The findings of the study were discussed in light of media convergence, with implications for developing media literacy education for the youth.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.209-231
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• 2015

The main purpose of this study is to develop and apply a means of connecting reading movement and Newspaper In Education (NIE) activities utilizing the voluntary participation and cooperation of local school districts and autonomous government entities. This is necessary to revitalize or systematize the environmental social life of reading newspapers and NIE activity. Literary or inquiry research will be initiated in this study in order to quantify the current or actual conditions of this connection, delineating the basic objectives of this study, and determining the developmental directions for continuing this study as related to the connection of reading movement and NIE activity. Anticipated study activities or major tasks are as follows. First, develop a variety of intended programs and learning materials necessary for each. Secondly, develop and establish corresponding online data and educational programs. Thirdly, a "cooperation" system must be established and training programs implemented reinforcing these ideas. And, lastly (and to gain wider acceptance), starting a public relations campaign to show or illustrate the benefits of this study and these intended research activities. In conclusion, if a connection between reading movement and NIE activity are fully established and periodically adjusted by means of continuing discussions on the merits or concerns based on the study findings, the full potential of the reading movement connection with NIE activity will be realized and achieved to its truest meaning and/or highest order.