• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.619-624
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• 2016

Social-aware video displays not only the relationships between characters but also diverse information on topics such as economics, politics and culture as a story unfolds. Particularly, the speaking habits and behavioral patterns of people in different situations are very important for the analysis of social relationships. However, when dealing with this dynamic multi-modal data, it is difficult for a computer to analyze the drama data effectively. To solve this problem, previous studies employed the deep concept hierarchy (DCH) model to automatically construct and analyze social networks in a TV drama. Nevertheless, since location knowledge was not included, they can only analyze the social network as a whole in stories. In this research, we include location knowledge and analyze the social relations in different locations. We adopt data from approximately 4400 minutes of a TV drama Friends as our dataset. We process face recognition on the characters by using a convolutional- recursive neural networks model and utilize a bag of features model to classify scenes. Then, in different scenes, we establish the social network between the characters by using a deep concept hierarchy model and analyze the change in the social network while the stories unfold.

• Knowledge Management Research
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• v.22 no.4
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• pp.1-26
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• 2021

Measuring the intangible asset has been vigorously studied for its importance. Especially, the value of character in media industry is difficult to quantitatively evaluate in spite of the industry's rapid growth. Recently, the Social Network Analysis (i.e., SNA) has been actively applied to understand human usage patterns in a media field. By using SNA methodology, this study attempts to investigate how the character network characteristics of media works are linked to human search behaviors. Our analysis reveals the positive correlation and causality between character network centralities and character search data. This result implies that the character network can be used as a clue for the valuation of character assets.

• The Journal of the Korea Contents Association
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• v.16 no.12
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• pp.551-561
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• 2016

A user influence discrimination scheme using big data from social networks is needed. In this thesis, we propose a user influence discrimination scheme considering reliability in social networks. The proposed scheme measures reliability scores through social activities and simplifies a social network by collecting only reliable users. It also derives user influence by considering direct and indirect influences that depends on network degree between users. As a result, the proposed scheme improves the expandability of the user influence. In order to show the superiority of the proposed scheme, we compare it with the existing scheme through performance evaluations in terms of reliability and user influence.

• Journal of Korean Academy of Nursing
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• v.30 no.3
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• pp.694-708
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• 2000

The main purpose of this study was to identify the relationship of self efficacy and social support to the psychosocial adjustment in people with epilepsy. Data were collected from October 1 to October 15, 1999 from 101 people with epilepsy who were being treated regularly at one of the university hospitals located in Seoul. The research instruments were a questionnaire to gather demographic and disease-specific data, the Epilepsy Psycho- Social Effects Scale developed by Chaplin et al(1990), the Epilepsy Self Efficacy Scale developed by DiIorio et al(1992a) and translated by Park(1999), the Norbeck Social Support Questionnaire developed by Norbeck et al(1981) and translated by Oh(1985). Data were analyzed using the SPSS program. The results are as follow : 1. Of the 14 psychosocial adjustment areas, 75 of 101 subjects experienced problems in ten or more areas and 28 in all 14 areas. The severity of the psychosocial adjustment problem was moderate or more in six areas. 2. The score for self efficacy was an average of 1103.86 out of a possible 1800, for social support 117.57 for total functional out of a possible 720, and 48.21 for total network out of a possible 264. There were an average of five people on the network. The main network people were parents, brothers and sisters, spouse, friends. 3. Of the 14 psychosocial adjustment areas, six areas correlated with self efficacy and 'problems with taking medication' area had a negative correlation with social support. In conclusion, people with epilepsy have various problems in psychosocial adjustment. Nursing interventions using self efficacy should be developed to improve psychosocial adjustment in people with epilepsy. Also, instruments and interventions for regimen-specific supports which are suitable for epilepsy should be developed.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.119-129
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• 2016

With the development of web, amount of information are generated in social web. Then many researchers are focused on the extracting and analyzing social issues from various social data. The proposed approach performed gathering the science data and analyzing with LDA algorithm. It generated the clusters which represent the social topics related to 'health'. As a result, we could deduce the relationship between science data and social issues.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• The Research Journal of the Costume Culture
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• v.32 no.1
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• pp.38-57
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• 2024

This study utilizes social big data to investigate the factors influencing the awareness, attitude, and behavior toward vegan fashion consumption among global and Korean consumers. Social media posts containing the keyword "vegan fashion" were gathered, and meaningful discourse patterns were identified using semantic network analysis and sentiment analysis. The study revealed that diverse factors guide the purchase of vegan fashion products within global consumer groups, while among Korean consumers, the predominant discourse involved the concepts of veganism and ethics, indicating a heightened awareness of vegan fashion. The research then delved into the factors underpinning awareness (comprehension of animal exploitation, environmental concerns, and alternative materials), attitudes (both positive and negative), and behaviors (exploration, rejection, advocacy, purchase decisions, recommendations, utilization, and disposal). Global consumers placed great significance on product-related information, whereas Korean consumers prioritized ethical integrity and reasonable pricing. In addition, environmental issues stemming from synthetic fibers emerged as a significant factor influencing the awareness, attitude, and behavior regarding vegan fashion consumption. Further, this study confirmed the potential presence of cultural disparities influencing overall awareness, attitude, and behavior concerning the acceptance of vegan fashion, and offers insights into vegan fashion marketing strategies tailored to specific cultures, aiming to provide vegan fashion companies and brands with a deeper understanding of their consumer base.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.791-800
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• 2023

This study was conducted to lay the foundation for creating a society safe from radiation by investigating the establishment of a radiation social safety net and the establishment of safety awareness and safety culture among citizens living in Busan. Data was collected through an online survey, and 200 copies of the survey were analyzed. Data were analyzed using SPSS Window Ver 28.0. To verify differences between groups, t-test and one way ANOVA were performed, and correlation analysis was performed to confirm the relationship between variables. In addition, multiple linear regression analysis was conducted to confirm the influence between variables. As a result, first, in terms of building a social safety net, citizens' safety awareness, and establishing a safety culture, the scores of the group with male gender, age in 20s, and high school graduation were found to be high. Among them, there was a statistical difference in gender at the significance level of .01 for building a social safety network and at the significance level of .05 for establishing a safety culture. In terms of occupation, there was a statistical difference between professionals and service workers at the significance level of .05 regarding the building of a radiation social safety network. Second, as a result of multiple regression analysis, it was found that 'local government radiation safety education', a subordinate factor in building a radiation social safety network, had a positive effect on citizens' safety awareness and establishment of a safety culture. Third, the results of the correlation analysis between the building of a social safety network, citizens' safety awareness, and establishment of a safety culture showed a positive correlation. Therefore, it is believed that a good radiation social safety network will have a positive impact on citizens' safety awareness and the establishment of a safety culture.

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.131-136
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• 2021

This research aims to analyse the practices adopted by social media users in the Kingdom of Saudi Arabia (KSA), specifically users of Facebook and Snapchat. To collect data from participants, a questionnaire was used, generating 915 responses. The analysis of the data shows a clear preference for Snapchat over Facebook in the KSA, where 89% of the participants have accounts on Snapchat compared to 66% of them with accounts on Facebook. Moreover, the preference for Snapchat over Facebook has been clearly shown in the daily usage of participants, where 83% of those with Snapchat accounts can be described as very active users. They have accessed their Snapchat accounts at least once a day compared to only 15% of Facebook users. Different reasons were provided by the participants explaining the practices they adopted. We believe that such research could help social media applications' designers and policy makers to understand the behaviour of users in the KSA when using social media applications and the rationale behind their behaviour and preferences. This understanding could help improve the performance of current applications and new ones.