• International Journal of Computer Science & Network Security
• /
• v.21 no.7
• /
• pp.305-316
• /
• 2021

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

• Asia pacific journal of information systems
• /
• v.31 no.2
• /
• pp.197-219
• /
• 2021

Social media platforms have become prominent channels for e-commerce, and the role of social network sites' (SNS) content marketing is expanding as a strategic marketing communication approach to attract and retain consumers and increase sales. In this study, we focused on South Korea market and explored the influence of linguistic complexity and informality on consumer engagement. In particular, we identified the importance of complexity, focusing on its negative effects, as well as the moderating effect of commerce features to minimize these effects. Specifically, content length, hashtags, long words, and average sentence length significantly and negatively impacted consumer engagement. The influence of emojis, an informality variable, was not statistically significant. Shoppable tags, a commerce feature that provides both advertising explicitness and shopping convenience, were a moderating factor in the influence of complexity. Our findings provide new insights for content marketing researchers, and have practical implications for social media managers and content developers.

• The Korean Journal of Community Living Science
• /
• v.20 no.1
• /
• pp.103-121
• /
• 2009

Increased consensus among gerontologists exist on the need to pay greater attention to the reciprocal relationship between the social and spatial in order to understand the construction of aged identity and everyday lives of old people. With urbanization, spaces are increasingly age-graded and as a consequence, urban elders are socially isolated from the community. In this study, we examine the social interaction patterns in various places specifically designated for the elderly, such as the Senior Center, Senior Welfare Center, and Hall for the Aged in Seoul. Main purpose of this study is to understand everyday life experiences of space the elderly people residing in the city go through. Data were gathered through qualitative, case study method. Results show that such spaces were important sites for social interaction for urban elderly who lacked social spaces after retirement and active parenting role. Also, it was shown that each place presents different contexts for social interactions and certain components of social class differences existed. Heterogeneity within the participants of each place was also observed. Quite strong stereotypes about certain places were also observed among the urban elders. Based on these results, importance of developing a 'community perspective' in the study of old age is discussed.

• Korean Security Journal
• /
• no.29
• /
• pp.301-336
• /
• 2011

This exploratory study aims to review the risks and threats of social network services(SNSs), particularly focusing upon the policing perspective. This paper seeks to acknowledge the present risk/danger of SNSs and the very significance of establishing a strategic framework to effectively prevent and/or control criminal misuse of SNSs. This research thus advocates that proactive study on security issues and criminal aspects of SNSs and preventive countermeasures can play a significant role in policing the networked society in the time of digital/internet age. Social network sites have been increasingly attracting the attention of entrepreneurs, and academic researchers as well. In this exploratory article, the researcher tried to define concepts and features of SNSs and describe a variety of issues and threats posed by SNSs. After summarizing existing security risks, the researcher also investigated both the potential threats to privacy associated with SNSs, such as ID theft and fraud, and the very danger of SNSs in case of being utilized by terrorists and/or criminals, including cyber-criminals. In this study, the researcher primarily used literature reviews and empirical methods. The researcher thus conducted extensive case studies and literature reviews on SNSs. The literature reviews herein cover theoretical discussions on characteristics, usefulness, and/or potential danger/harm of SNSs. Through the literature review, the researcher also concentrated upon being able to identify a strategic framework for law enforcement to effectively prevent criminal misuse of SNSs The limitation of this study can be lack of statistical data and attempts to examine previously un-researched area in the field of SNS and its security risks and potential criminal misuse. Thus, to supplement this exploratory study, more objective theoretical models and/or statistical approaches would be needed to provide law enforcement with sustainable policing framework and contribute to suggesting policy implications.

• The Journal of Information Systems
• /
• v.29 no.3
• /
• pp.103-117
• /
• 2020

Purpose Recently, various issues related to toxic comments on web portal sites and SNS are becoming a major social problem. Toxic comments can threaten Internet users in the type of defamation, personal attacks, and invasion of privacy. Over past few years, academia and industry have been conducting research in various ways to solve this problem. The purpose of this study is to develop the deep learning modeling for toxic comments classification. Design/methodology/approach This study analyzed 7,878 internet news comments through CNN classification modeling based on Highway Network and OOV process. Findings The bias and hate expressions of toxic comments were classified into three classes, and achieved 67.49% of the weighted f1 score. In terms of weighted f1 score performance level, this was superior to approximate 50~60% of the previous studies.

• Industrial Engineering and Management Systems
• /
• v.12 no.2
• /
• pp.130-142
• /
• 2013

Social Networking Service (SNS) is prevailing rapidly in Japan in recent years. The most popular ones are Facebook, mixi, and Twitter, which are utilized in various fields of life together with the convenient tool such as smart-phone. In this work, a questionnaire investigation is carried out in order to clarify the current usage condition, issues and desired functions. More than 1,000 samples are gathered. Bayesian network is utilized for this analysis. After conducting the sensitivity analysis, useful results are obtained. Differences in usage objectives and SNS sites are made clear by the attributes and preference of SNS users. They can be utilized effectively for marketing by clarifying the target customer through the sensitivity analysis.

• Journal of KIISE
• /
• v.43 no.1
• /
• pp.47-53
• /
• 2016

While the Internet develops rapidly, a huge amount of image data collected from smart phones, digital cameras and black boxes are being shared through social media sites. Generally, social images are handled by tagging them with information. Due to the ease of sharing multimedia and the explosive increase in the amount of tag information, it may be considered too much hassle by some users to put the tags on images. Image retrieval is likely to be less accurate when tags are absent or mislabeled. In this paper, we suggest a method of extracting tags from social images by using image content. In this method, CNN(Convolutional Neural Network) is trained using ImageNet images with labels in the training set, and it extracts labels from instagram images. We use the extracted labels for automatic image tagging. The experimental results show that the accuracy is higher than that of instagram retrievals.

• Journal of Korean Academy of Nursing
• /
• v.51 no.1
• /
• pp.68-79
• /
• 2021

Purpose: This study aimed to analyze the mass and social media contents and structures related to particulate matter before and after the policy enforcement of the comprehensive countermeasures for particulate matter, derive nursing implications, and provide a basis for designing health policies. Methods: After crawling online news articles and posts on social networking sites before and after policy enforcement with particulate matter as keywords, we conducted topic and semantic network analysis using TEXTOM, R, and UCINET 6. Results: In topic analysis, behavior tips was the common main topic in both media before and after the policy enforcement. After the policy enforcement, influence on health disappeared from the main topics due to increased reports about reduction measures and government in mass media, whereas influence on health appeared as the main topic in social media. However semantic network analysis confirmed that social media had much number of nodes and links and lower centrality than mass media, leaving substantial information that was not organically connected and unstructured. Conclusion: Understanding of particulate matter policy and implications influence health, as well as gaps in the needs and use of health information, should be integrated with leadership and supports in the nurses' care of vulnerable patients and public health promotion.

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

• Journal of Internet Computing and Services
• /
• v.17 no.1
• /
• pp.83-89
• /
• 2016

This study aimed to examine how gender and regional differences affect the relationships between SNS use and social capital. By analyzing a large set of data from Korean teenagers, significant roles of gender and regional differences could be found. In regards to gender difference, the most notable finding was the negative effects of SNS use on bonding and bridging social capital among male teenagers. Furthermore, it was found that such negative effects of SNS use were significant particularly among urban teenagers. These findings theoretically contribute to broadening the understanding of the relationships between SNS use and social capital.