• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.404-415
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• 2022

The purpose of this study is to propose considerations to help actual application based on the characteristics of the online art-based peer supervision execution process. Colleagues in the clinical art therapy doctoral program, including the researcher, attempted to repeatedly identify problems and apply improvements in the implementation process as research participants, and qualitatively analyzed the various data collected in the process. Looking at the characteristics of the analysis results, extensibility of materials and space was confirmed in terms of 'art-based' and initiative, convenience, and speed in terms of 'online'. The considerations identified through this are as follows. First, 'pre-structuring' should be based on clear boundaries and setting, prior consultation of the group, and self-directed preparation and attitude. Second, for the 'structural aspect of art', space and media to help immersion through creation, and stable implementation structure should be established. Third, in the 'technical aspect', it is necessary to apply a method that can deliver a work of art and a method that can communicate the creator's clear intention. Lastly, for the 'ethical aspect', it is necessary to use online software in accordance with the minimum security standards and to make efforts to repeatedly maintain confidentiality. This study is meaningful in that it suggested a practical method for maintaining the professional competence of art therapists and expanding networks among art therapists in various situations including pandemics.

• Research in Community and Public Health Nursing
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• v.12 no.3
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• pp.795-814
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• 2001

To evaluate the effect of sex education on middle school students' access to the obscene online computer and video film contents. 154 students were selected as experimental group. and 154 students were selected as control group, sampled randomly from Andong. Kyungbook, Korea. An analysis was performed. A non-equivalent control group pre test-post test research design was used. The data were collected from April 2nd to April 19th. 2001. A pre-survey was done on general characteristics and the condition of accessing obscene online computer and video film contents on both experimental and control group. From the survey results information. sex education contents were put together. The researcher organized 3 ready-made sex education program and explained to the four school health nurses about the ready-made sex education program step by step and they educated their selected students with three classes of 45 minutes lecture. Two weeks after the last lecture, a post-test was conducted. Four weeks from the last lecture, another post-test was conducted. The existing studies by Choi Yongseon(1998) and Kim Hyeok(1998) were reviewed and two professors in the department of community health nursing advised on the study questionnaire writing. An SPSS Win 10.0 was used. The data of respondents' general characteristics were analyzed using frequency and percentage. $X^2$ test was used to verify the homogeneity of the experimental group and the control group. Repeated Measures ANOVA was used to find out whether sex education had an effect on the awareness of obscene online computer and video film contents and under-age prostitution through the online computer networks. and time and frequency of access to the obscene online computer and video film contents. The results of the study are as follow. 1. The results of the verification of homogeneity between the experimental group and the control group showed that there was no significant difference between the experimental group and the control group. 2. The first hypothesis, 'the experimental group which received sex education would have a higher level of awareness of accessing obscene contents than the control group which did not receive the education' was supported at p<0.0001. 3. The second hypothesis. 'the experimental group which received sex education would have a higher level of awareness of underage prostitution on computer networks than the control group which did not receive the education' was supported at p<0.05. 4. The third hypothesis, 'the experimental group which received sex education would spend time less accessing obscene video and computer contents than the control group which did not receive the education' was rejected at p>.05. 5. The 4-1 hypothesis. 'the experimental group which received sex education would access obscene computer contents less frequently than the control group which did not receive the education' was supported at p<0.0001. 6. The 4-2 hypothesis, 'the experimental group which received sex education would access obscene video contents less frequently than the control group which did not receive the education' was supported at p<0.0001. In conclusion, a systematic step-by-step sex education program should be developed to protect middle school students from the harmful online computer and video film access. An effective teaching material for sex education should be prepared to decrease middle school students' access to obscene online computer and video film contents.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.