• Journal of Information Technology Services
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• v.14 no.3
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• pp.33-48
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• 2015

Recently, many users frequently share their opinions on diverse issues using various social media. Therefore, many governments have attempted to establish or improve national policies according to the public opinions captured from the various social media. In this paper, we indicate several limitations of traditional approaches for analyzing public opinions about science and technology and provide an alternative methodology to overcome the limitations. First of all, we distinguish science and technology analysis phase and social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we apply a start list and a stop list successively to acquire clarified and interesting results. Finally, to identify most appropriate documents fitting to a given subject, we develop a new concept of logical filter that consists of not only mere keywords but also a logical relationship among keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discovering core issues and public opinions from 1,700,886 documents comprising SNS, blog, news, and discussion.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.601-605
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Millions of users have integrated these sites into their daily practices to communicate with online people. In this paper, we propose an efficient face annotation and retrieval system under SNS. Since the system needs to deal with a huge database which consists of an increasing users and images, both effectiveness and efficiency are required, In order to deal with this problem, we propose a face annotation classifier which adopts an online learning and social decomposition approach. The proposed method is shown to have comparable accuracy and better efficiency than that of the widely used Support Vector Machine. Consequently, the proposed framework can reduce the user's tedious efforts to annotate face images and provides a fast response to millions of users.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.22-27
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• 2019

Along with the universalization of smartphones, smartphone addiction is becoming a physical and mental social problem. The purpose of this study was to investigate the relevance of the problems caused by addiction in 300 adolescents, adults and the elderly. The results showed that the use of SNS and messenger were most related to the negative factors such as health problems, depression, antisocial, schizophrenia, lower self-esteem, and lower social expectation. In addition, games and videos were analyzed to have relatively low negative problems. Focusing on the high addiction rate, the researcher further analyzed the preference for problem solution and discussed the improvement measures for smartphone addiction reduction.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.588-600
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• 2019

Each year Malaria affects over 200 million people worldwide. Particularly, African continent is highly hit by this disease. According to many researches, this continent is ideal for Anopheles mosquitoes which transmit Malaria parasites to thrive. Rainfall volume is one of the major factor favoring the development of these Anopheles in the tropical Sub-Sahara Africa (SSA). However, the surveillance, monitoring and reporting of this epidemic is still poor and bureaucratic only. In our paper, we proposed a method to fast monitor and report Malaria instances by using Social Network Systems (SNS) and precipitation volume in Nigeria. We used Twitter search Application Programming Interface (API) to live-stream Twitter messages mentioning Malaria, preprocessed those Tweets and classified them into Malaria cases in Nigeria by using Support Vector Machine (SVM) classification algorithm and compared those Malaria cases with average precipitation volume. The comparison yielded a correlation of 0.75 between Malaria cases recorded by using Twitter and average precipitations in Nigeria. To ensure the certainty of our classification algorithm, we used an oversampling technique and eliminated the imbalance in our training Tweets.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.1019-1035
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• 2020

This study examines the millennial generation, who express themselves and share information on social media after experiencing constantly changing 'hot places' (places of interest) in contemporary cities, with the goal of analyzing space consumption behaviors. Data were collected via an Instagram crawler application developed with Python 3.4 administered to 19,262 posts using the term 'hot places' from November 1 and December 15, 2019. Issues were derived from a text mining technique using Textom 2.0; in addition, semantic network analysis using Ucinet6 and the NetDraw program were also conducted. The results are as follows. First, a frequency analysis of keywords for hot places indicated words frequently found in nouns were related to food, local names, SNS and timing. Words related to positive emotions felt in experience, and words related to behavior in hot places appeared in predicate. Based on importance, communication is the most important keyword and influenced all issues. Second, the results of visualization of semantic network analysis revealed four categories in the scope of the definition of "hot place": (1) culinary exploration, (2) atmosphere of cafés, (3) happy daily life of 'me' expressed in images, (4) emotional photos.

• Food Science and Industry
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• v.50 no.3
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• pp.33-38
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• 2017

One noticeable thing about the recently opened 'Starfield Hanam' and 'Hyundai Department Store (Pangyo)' is consumer's interest and positive response to their hosted food brands ranging from restaurants, dessert cafes and coffee shops. Department store and shopping complex, so-called aggregation of lifestyle are making the most out of food brands as a differentiation strategy and consumer's interest on it act as a barometer for current consumption trend. Along with the high interest on food market, changes in lifestyle, such as increasing ratio of two or less households, advent of multiple communication channels as SNS, deluge of information and gradually developing individualism, are creating needs for convenient but high quality eating culture. This need contributed in transforming the product family which was once famous as 'Instant Food' into a 'Home Meal Replacement (HMR)'. Since local food companies are striving to keep pace with the trend and actively penetrating HMR market, regardless of long-term recession, the Korean domestic food market is steadily growing with a bright future.

• The Research Journal of the Costume Culture
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• v.30 no.5
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• pp.766-778
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• 2022

Image-oriented information is becoming increasingly important on social networking services (SNS); the background of this trend is the popularity of selfies. Currently, camera applications using augmented reality (AR) and artificial intelligence (AI) technologies are gaining traction. An AR camera app is a smartphone application that converts selfies into various interesting forms using filters. In this study, we investigated the change of keywords according to the time flow of selfies in Goolgle News articles through semantic network analysis. Additionally, we examined the effects of using an AR camera app on appearance satisfaction and self-esteem when taking a selfie. Semantic network analysis revealed that in 2013, postings of specific people were the most prominent selfie-related keywords. In 2019, keywords appeared regarding the launch of a new smartphone with a rear-facing camera for selfies; in 2020, keywords related to communication through selfies appeared. As a result of examining the effect of the degree of use of the AR camera app on appearance satisfaction, it was found that the higher the degree of use, the higher the user's interest in appearance. As a result of examining the effect of the degree of use of the AR camera app on self-esteem, it was found that the higher the degree of use, the higher the user's negative self-esteem.

• Journal of Information Technology Applications and Management
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• v.29 no.1
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• pp.59-70
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• 2022

Recently, in platforms such as YouTube and Instagram, virtual characters resembling human life become the main characters, produce various contents, breathe with the public, and create the era of virtual humans. For example, existing game characters appear as virtual characters with unique AUs, or AI characters created by reflecting the public's preferences are actively communicating with the public through advertisements and SNS activities. As the consumption of video content through smart devices increases significantly in the post-corona era, virtual influencers are being used as all-round entertainers because there is little risk of personality controversy or production cost. there is a trend In this study, we investigated the characteristics of the case of being active as an influencer among the activities of a virtual character, and how the interactive aspect of the influencer appears by identifying the current situation through major cases. Combining this, based on the analysis of the influence of virtual influencers, the parts that producers should recognize are derived, and the differentiated characteristics of interactive virtual influencers are summarized. In addition, the difficulties of virtual influencers were investigated and problems were identified, and for the development of the content industry, a more favorable method for interaction was presented and suggestions were made to secure inner sincerity.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.1-11
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• 2017

In this paper, I analyzed the cause that girl' ICT literacy score was hiegher than boy's score in middle school after 2010. KERIS had sampled 1% of whole middle school students and measured their ICT level. Therefore, I analyzed the correlation by gender between ICT literacy score and the using habit of ICT based on that result. As a result, the girl's score was higher than the boy's score in field of creating or editing documents, searching information for homework and study, accessing to on-line dictionary for study and enjoying SNS. Also, that difference between girl and boy had little correlation with ICT literacy score. Therefore, I proposed educational method for ICT literacy learning based on the difference of habit to use ICT between boys and girls.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.29-34
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• 2016

Nowadays, real-time devices that provide health care for a companion animal is being developed by IoT technology and its demand such as smart puppy tag is increasing. However, it is difficult for IoT devices of companion animals to process complex nature due to miniaturized hardware and constructive nature. There is a clear limit to custom advanced features like health care implementation. This paper designs an integrated platform with statistical analysis which makes it possible to customized services such as feed production, pharmaceutical production, and health care for each companion animal. Middleware that collects sensor information, customer's spending pattern and information from Social Network Service is also designed by making use of IoT devices which companion animals wear. Furthermore, the paper designed data analyzer which analyzes and refines data from collected information that can be applied to personalized services.