• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.129-140
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• 2019

In the IoT environment, there is a huge amount of heterogeneous devices with limited capacity. Existing trust evaluation methods are not adequate to accommodate this requirement due to the limited storage space and computational resources. In addition, since IoT devices are mainly human operated devices, the trust evaluation should reflect the social relations among device owners. There is also a need for a mechanism that reflects the tendency of the trustor and environmental factors. In this paper, we propose an adaptable trust evaluation method for SOA-based IoT system to deal with these issues. The proposed model is designed to minimize the confidence bias and to dynamically respond to environmental changes by combining direct evaluation and indirect evaluation. It is expected that it will be possible to secure trust through quantitative evaluation by providing feedback based on social relationships.

• Fashion & Textile Research Journal
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• v.18 no.1
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• pp.48-62
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• 2016

Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.453-462
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• 2016

Since the Internet provides a way of expressing and sharing Internet users' mindsets, corporate marketers want to acquire measurable and actionable insights from web data. In the past, companies used to analyze the attitude, satisfaction, and loyalty of consumers toward their brands using survey data, whereas nowadays this is done using the big data extracted from Social Network Services. In this study, we propose a framework for clustering brand names using the social metrics gathered on social media. We also conduct a case study of the automobile industry to verify the feasibility of the proposed framework. We calculate the brand name distance for each pair of brand names based on the total number of times that they are mentioned together. These distances are used to project the brand name onto a 3-dimensional space using multidimensional scaling. After the projection, we found the clusters of brand names and identified the characteristics of each cluster. Furthermore, we concluded this paper with a discussion of the limitations and future directions of this research.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.1-9
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• 2019

The purposes of the study are to investigate Koreans' perception about Vietnam by analyzing social big data and to seek changing direction in perception. For the purposes, the texts about Vietnam in Naver Blog and Twitter and the number of search and click for Vietnam in Naver were analyzed by Social Metrics of Daum Soft and Datalab of Naver. The study also analyzed the annual change of their interest in Vietnam based on social media. The results showed that Koreans still remember the Vietnam war, have a positive emotion toward Vietnam, and view Vietnam as a country where we can gain mutual benefit by exchange. The findings also indicated that Koreans perceive Vietnam as a favorite tourist spot regardless of age. Meanwhile, children under 12 showed a different pattern of an annual change in perception. It might be a positive sign that Koreans' interest region toward Vietnam would be diversified because children under 12 would be the central axis of cultural contents.

• Journal of Information Science Theory and Practice
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• v.4 no.1
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• pp.6-20
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• 2016

Scholarly communication plays a significant role in the development and dissemination of research outputs in library and information science (LIS). This study presents findings from a survey which examines the key attributes that characterize the publishing by Pakistani LIS scholars, i.e. academics and professionals, in national journals. A pilot-tested, electronic questionnaire was used to collect the data from the target population. 104 respondents (or 69.3% of target) provided feedback on areas such as number of articles published, number of citations, and the nature of any collaboration with other authors. The findings of this survey revealed that, among the various designated regions of Pakistan, the Punjab region was the most highly represented. In articles published in national journals, there was a clear preference among all respondents to collaborate with at least one other author. The citation metrics for LIS articles in national journals were relatively low (30.22%), which aligns with Scimago’s Journal and Country Rankings. The uptake of social scholarly networks mirrors international trends. Respondents were asked to score factors which could impact negatively on their ability to undertake research and/or publish the results. The study recommends that concerned stakeholders work together, as appropriate, to address concerns. In addition, it recommends that further research be undertaken to define patterns of Pakistani co-authorship in the social sciences.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1017-1027
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• 2022

Development of social overhead capital (SOC) requires huge national finance, and performance issues such as cost-efficiency, safety, and environment have been constantly raised. However, currently each construction client has limited access to its own projects' performance without analytic methodology for industry-level comparisons and benchmarking for improvement. To overcome this problem, this study proposes a comprehensive performance analysis framework for post-evaluation of large-scale construction projects. To this end, this study performed a case study of advanced countries (the U.S., the U.K. and Japan) and consultation with related experts to develop a tailored performance analysis framework for the Post- Construction Evaluation and Management system in Korea. The developed framework covers three categories (project performance, project efficiency, and ripple effect), nine areas (cost, schedule, change, safety, quality, demand, benefit-cost ratio, civil complaint, and defect), and 31 detailed metrics. Using industry-level project performance database and statistical techniques, the proposed framework can be used not only to diagnose excellent and unsatisfactory performance areas for completed construction projects, but also to provide reference data for future similar projects. This study can contribute to the improvement of clients' performance management practices and effectiveness of construction projects.

• The Journal of Industrial Distribution & Business
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• v.14 no.1
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• pp.1-11
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• 2023

Purpose: The purpose of the current research is to investigate the contribution of the sports and leisure sector to raising elderly citizens' quality of life. Through this investigation, the sport and leisure sector may give seniors a sense of safety and security by creating a safe atmosphere in which they can engage in activities and feel a part of their communities. Research design, data and methodology: Literature data were extracted from previous studies between the role of the sports leisure sector and living quality for senior citizens using a standardized data extraction form by two independent reviewers after articles have been included in the review. Each study's data extraction includes details on the study's design, exposure, outcome metrics, and findings. Results: Based on the qualitative textual approach, the present author had figured out total four Functions assumed as follows: (A) Physical Activity and Exercise, (B) Socialization and Interaction, (C) Opportunities for Learning and Development, and (4) Emotional Wellbeing. Conclusions: All in all, professionals should try to give elders chances for social interaction and peer participation in order to foster a feeling of community and belonging. This might entail setting up groups or leagues for elders to engage in meaningful social activities, like hiking or sports.

• Culinary science and hospitality research
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• v.23 no.7
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• pp.1-10
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• 2017

This study proposed SNS big data analysis method of food service industry in the 4th industrial revolution. This study analyzed the keyword of the fourth industrial revolution by using Google trend. Based on the data posted on the SNS from January 1, 2016 to September 5, 2017 (1 year and 8 months) utilizing the "Social Metrics". Through the social insights, the related words related to cooking were analyzed and visualized about attributes, products, hobbies and leisure. As a result of the analysis, keywords were found such as cooking, entrepreneurship, franchise, restaurant, job search, Twitter, family, friends, menu, reaction, video, etc. As a theoretical implication of this study, we proposed how to utilize big data produced from various online materials for research on restaurant business, interpret atypical data as meaningful data and suggest the basic direction of field application. In order to utilize positioning of customers of restaurant companies in the future, this study suggests more detailed and in-depth consumer sentiment as a basic resource for marketing data development through various menu development and customers' perception change. In addition, this study provides marketing implications for the foodservice industry and how to use big data for the cooking industry in preparation for the fourth industrial revolution.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.164-172
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• 2023

In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.