• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big 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. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Economic and Environmental Geology
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• v.47 no.4
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• pp.431-439
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• 2014

The purposes of this research were to investigate the enrichment of metal-reducing bacteria from KURT groundwater and the identification of the microbial diversity by 16S rRNA as well as to examine microbial Fe(III)/Mn(IV) reduction and to analyze morphological features of interactions between microbes and precipitates and their mineralogical composition. To cultivate metal-reducing bacteria from groundwater sampled at the KURT in S. Korea, different electron donors such as glucose, acetate, lactate, formate, pyruvate and Fe(III)-citrate as an electron accepter were added into growth media. The enriched culture was identified by 16S rRNA gene sequence analysis for the diversity of microbial species. The effect of electron donors (i.e., glucose, acetate, lactate, formate, pyruvate) and electron acceptors (i.e., akaganeite, manganese oxide) on microbial iron/manganese reduction and biomineralization were examined using the 1st enriched culture, respectively. SEM, EDX, and XRD analyses were used to determine morphological features, chemical composition of microbes and mineralogical characteristics of the iron and manganese minerals. Based on 16S rRNA gene analysis, the four species, Fusibacter, Desulfuromonas, Actinobacteria, Pseudomonas sp., from KURT groundwater were identified as anaerobic metal reducers and these microbes precipitated metals outside of cells in common. XRD and EDX analyses showed that Fe(III)-containing mineral, akaganeite (${\beta}$-FeOOH), reduced into Fe(II)/Fe(III)-containing magnetite ($Fe_3O_4$) and Mn(IV)-containing manganese oxide (${\lambda}-MnO_2$) into Mn(II)-containing rhodochrosite ($MnCO_3$) by the microbes. These results implicate that microbial metabolism and respiratory activities under anaerobic condition result in reduction and biomineralization of iron and manganese minerals. Therefore, the microbes cultivated from groundwater in KURT might play a major role to reduce various metals from highly toxic, mobile to less toxic, immobile.

• Journal of Distribution Science
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• v.12 no.4
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• pp.5-9
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• 2014

Purpose - The purpose of this study was to compare and contrast the applicability and effectiveness of both teukyakmeip contracts of Korea and consignment contracts of the United State to demonstrate the effectiveness and practicability of teukyakmeip in Korea. These are popular contract agreements between large retailers and their suppliers and vendors. In recent years, teukyakmeip was critically examined and scrutinized by the politicians, the media, and the public of Korea. Consequently, this paper focusesheavily on identifying and analyzing different types of contract agreements between large retailers and their suppliers that currently exist in Korea and compares and contrasts those analyzed contract agreements with teukyakmeip. The article also comparesand contrasts teukyakmeip with the consignment agreements of the United States to identify similarities and differences. Research design, data, and methodology - This study is a descriptive study and has used personal interviews to collect and analyze the data. This study also fits the definition of the case study wherein it is entirely focused on investigating a real-life event: analyzing and examining contract agreements in the distribution industry. Both randomly selected management and vendor representatives from the three major department stores, Lotte, Hyundai, and Shinsegae, in Korea were interviewed between July and September 2013. The analysis of the consignment agreement was conducted based on existing secondary data. Results - Although the evidence of the abuse of teukyakmeip and consignment by large retailers from both countries clearly exists, the findings suggestthat both contract agreements would remain as the most relevant and effective legal contracts between large retailers and their suppliers. Based on the comparisonanalysis of teukyakmeip and consignment, both contracts indicated that suppliers are fully responsible for inventory and inventory management. If sales person is necessary for promoting special product, then suppliers are responsible for providing a sales person and their wages under both contracts. However, American department stores, those located outside urban area, tend to use their own employees to perform special product and sales promotion. The retailersare fully responsible for any interior or floor design or redesign of the retail store to accommodate the products from vendors under consignment; however, both suppliers and retailers share the cost of designing and redesigning the interior to accommodate vendors'products under teukyakmeip. Suppliers are responsible for pricing and supplying the quantity of the products under both agreements. Both contracts allow special sales commission as long as vendors agreed. Vendors use this special commissionto introduce their new products or apply market penetration strategy. Conclusions -The findings of this study showed the changing pattern of contract agreements between large retailers and their suppliers from both countries. Furthermore, this study evidently generated policy implications of teukyakmeip which recently became the major social issue in Korea and attracted many policymakers to gain political points by criticizing the teukyakmeip system and the large retailers. The findings of the study would be valuable to policy makers in making appropriate decisions and to large retailers and vendors in making beneficial agreements. The major implication of this study is that teukyakmeip and consignment agreements include very similar or almost identical characteristics, and they are popular among department stores and suppliers. The issue of abolishing teukyakmeip in Korea needs to be examined cautiously because teukyakmeip is the best one available at the moment, and the study suggests that no one benefits from abolishing this system.

• Journal of Bio-Environment Control
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• v.27 no.2
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• pp.140-146
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• 2018

This research was conducted to determine the influence of incorporation levels of sulfur into a coir dust+pine bark medium (1:1, v/v) on the changes in the bicarbonate ($HCO_3{^-}$) concentrations and pH of soil solution, crop growth, and nutrient uptake of 'Ssanta' strawberry. In the preparing of the mixed medium, sulfur powder was added with the rate of 0 (control), 0.23, 0.45, 0.90, and $1.80g{\cdot}L^{-1}$ and Hoagland nutrient solution containing $240mg{\cdot}L^{-1}$ $HCO_3{^-}$ was supplied during the crop cultivation. The growth measurements and tissue analysis for the determination of nutrient contents were carried out 140 days after solution application and the soil solution analysis was performed every two weeks. As the level of sulfur was elevated, the overall growth of mother plants became better showing that the growth indexes except chlorophyll contents were the lowest in control treatment but the statistical differences were not found among the three treatments of $0.45g{\cdot}L^{-1}$ or higher sulfur. The higher the levels of sulfur incorporation, the higher the occurrence of runners and the growth of daughter plants. The length of the runners and the number of daughter plants occurred per mother plants were higher in the treatments of 0.90 and $1.80g{\cdot}L^{-1}$ than the three treatments of 0, 0.23, and $0.45g{\cdot}L^{-1}$, but the statistical differences were not observed between the 0.90 and $1.80g{\cdot}L^{-1}$ treatments. The rose of pH and $HCO_3{^-}$ concentrations in soil solution of root media continued all the cropping period, but those decreased slightly in the treatments of $0.90g{\cdot}L^{-1}$ or higher. The soil solution concentrations of $K^+$ and $PO_4{^3-}$ in the treatments of 0.90 and $1.80g{\cdot}L^{-1}$ was lower than those in other treatments and the statistical differences in the $Ca^{2+}$ and $Mg^{2+}$ concentrations were not observed among all treatments. The nutrient contents in tissue analyzed in this experiment were the lowest in the control treatments and those increased as incorporation rates of sulfur were elevated. Above results indicated that when 'Ssanta' strawberry is grown hydroponically and the root medium is coir dust and the pine bark (5:5, v/v) mix, the sulfur incorporation rate as pre-planting fertilizer has to be higher than $0.9g{\cdot}L^{-1}$ root medium to reduce the $HCO_3{^-}$ injury.

• Journal of Bio-Environment Control
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• v.27 no.2
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• pp.173-179
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• 2018

Investigation of the optimum levels of pre-plant nitrogen for raising of hot pepper (cv. Nokkwang) plug seedlings was the objective of this research. To achieve this, the pre-plant nitrogen levels were varied to 0, 100, 250, 500, 750, 1,000, and $1,500mg{\cdot}L^{-1}$ and the other essential nutrients were controlled to equal concentrations in all treatments. All the fertilizers were added during the formulation of the mixed medium of coir dust, peatmoss, and perlite with the ratio of 35, 35, and 30% (v/v/v). The root medium containing pre-plant fertilizer was packed into 50-cell plug trays and seeds were sown. The measurement of pH and EC in every week, soil solution analysis for nutrients in week 0, 3, and 7 and growth measurements as well as tissue analysis for nutrient contents in week 7 were conducted. The pHs measured before seed sowing did not show significant differences, but the differences among treatments became significant as seedlings grow bigger. The soil solution ECs were significantly different among treatments in week 0 and these differences were diminished by degrees after week 3, resulting in no significant differences among treatments in week 7. The trends in changes of $NH_4-N$, $NO_3-N$, and other the macro-element concentrations in soil solution of root media were similar to those of ECs. The treatments of 500 and $750mg{\cdot}L^{-1}$ N were more effective than other treatments on seedling growth. The seedling growths in the treatments containing higher N than $1,000mg{\cdot}L^{-1}$ and control were severely suppressed. The elevated pre-plant N concentrations in the root medium resulted in the increase of tissue N contents. The treatments of 500 and $750mg{\cdot}L^{-1}$ N shown the highest seedling growths had 5.13% and 5.31%, respectively, in tissue N contents based on the dry weight of above ground tissue at week 7. The results of this study indicated that the optimum level of pre-plant N is 500 to $750mg{\cdot}L^{-1}$ for the raising of hot pepper plug seedlings.

• Korean Security Journal
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• no.50
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• pp.175-206
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• 2017

The current study described the history of Islamic extremism and the recent expansion of international Islamic extremism in Indonesia. For doing so, both content analysis of the existing written documents and qualitative interviews were conducted. For the content analysis, media reports and research articles were collected and utilized. For qualitative interviews, Indonesian students and workers in Korea, Korean spouses married to Indonesian, and Korean missionaries in Indonesia were contacted and interviewed. Qualitative interview was conducted between 30 minutes and 2 hours. On the spot, interviews were recorded and later transcribed into written documents. Due to the difficulty of identification of population and the uneasiness of accessability to th study subjects, convenient sampling and snowball sampling were used. According to the results, Islamic extremism in Indonesia had a deep historical root and generally shared similar historical experience with other muslim countries such as Afghanistan, Pakistan, Egypt, and Saudi Arabia where Islamic extremism was deeply rooted in. That is, Islamic extremism began as a reaction to the western imperialism, after independence, Islamic extremism elements were marginalized in the process of construction of the modern nation-state, and Islamic extremist movement was radicalized and became violent during the Soviet-Afghan War. In addition, after 9.11, Islamic extremism in Indonesia was connected to international Islamic extremism network and integrated into such global movement. Such a historical development of Indonesian Islamic extremism was quite organized and robust. Meanwhile, the eastward infiltration and expansion of international Islamic extremism such as IS and Al Qaeda was observed in Indonesia. Particularly, such a worrisome expansion was more clearly visible in the marginalized and underdeveloped countrysides in Indonesia. Such expansion in Indonesia could negatively affect on the security of South Korea. Geographically, Indonesia is proximate to South Korea. This geographical proximity could be a direct security threat to the Korean society, as if Islamic extremism in North Africa and Middle East becomes a direct security threat to Europe. Considering the presence of a large size of Indonesian immigrant workers and communities in South Korea, such a concern is very realistic. The arrest of an Indonesian Islamic extremism supporter in November, 2016, could be a harbinger of the coming trend of Islamic extremism expansion inside South Korea. The Indonesian Islamic community in South Korea could be a passage of Indonesian Islamic extremism into the South Korean society. In this context, it is timely and necessary to pay an attention to the recent trend of Islamic extremism expansion in Indonesia.

• Korean Journal of Weed Science
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• v.7 no.3
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• pp.265-279
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• 1987

About 140 weed species belonging to 42 families occurring in summer were observed in Ulreung island. The Compositae was the most wildely occurring family covering 27 weed species, followed by 21 species in Graminae, 9 in Polygonaceae, 7 in Leguminosae, and 7 in Labiatae etc. In terms of the lands classified, about 60 species in 26 families were observed in the cultivated and the medical crops grown areas, respectively, and 116 species in 40 families occurred in the non-cultivated land like the vicinity of the cultivated area and 94 species in 34 families in the valley. No. of species and families were much greater in the non-cutivated land than those of the cultivated one. The most dominant weed species in both the cultivated and its vicinity in Ulreung island were Digitaria sanguinalis, followed by Portulaca oleracea, Polygonum hydropiper, Equisetum arvensis, Artemisia princeps, Commetina communis, Setaria viridis in order. Community analysis was done by the method of Toyohara in two cultivated lands such as the general crop land and the medical herb crop grown land, and two non-cultivated areas such as the vicinity of the cultivated land and valley. The cultivated land consisted of the communites of P. hydropiper and Cyperus amuricus, including Bidens tripartita in P. hydropiper community. The medical crop grown land composed of three major communities like P. hydropiper, Amaranthus mangostanus and Sonchus asper in which A. mangostanus and S. media were presented in the ecoton, indicating community being transiting. In the non-cultivated areas like the vicinity of crop land, the communities of Erigeron annuus, P. oleracea, and Oxalis corniculata were dominant, and Dystaenia takeshimana was included in the community of E. annuus and Stellan'a aquatica in P. oleracea community. In the valley, Ranunculus quelpaertensis community was existed in between the communities of Sonchus asper and Plantago asiatica.

• Journal of Nutrition and Health
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• v.51 no.4
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• pp.295-306
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• 2018

Purpose: Koreans' internet and smartphone usage hours are steadily increasing and the dependence of young people on smartphones is causing social problems. Therefore, this study was conducted to examine health and dietary habits, as well as hair mineral contents according to the level of dependence of smartphone use among adolescents to clarify the interrelation of smartphone dependence, lifestyle, dietary behavior, and mineral nutrition status. Methods: A total of 80 smartphone-addicted adolescents participated in this study and were divided into three groups (general, potential and danger group) according to smartphone dependence. The subjects' lifestyles and dietary behaviors were then surveyed, and hair mineral contents were analyzed. Results: Higher smartphone dependence was associated with lower average weekly sleeping time and later first smoking age. In the danger group, the rate of eating fast and the rate of snacking twice a day was also relatively high. Parents (45.0%) and mobile (30.0%) were the factors having the greatest influence on an individual's dietary behavior. In the hair mineral analysis, all subjects had lower selenium concentrations and higher lead concentrations than normal. In addition, the levels of aluminum in the danger group were higher than in the normal range and the highest among the three groups. Conclusions: It is necessary to guide adolescents to use smartphones correctly and manage dietary habits. In addition, careful attention is needed the mineral nutritional status of smartphone-addicted adolescents.