• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.109-116
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• 2020

Social media is growing rapidly as a means of promoting artists' artworks and a channel for sales. However, since social media is not fundamentally a platform designed for trading, it has various limitations that make it difficult to ensure trust and security in carrying out transactions. In this paper, it is proposed interoperability between social media and blockchain-based smart contract system that can record and preserve the artist's profile, information related to artworks and details of the contract on the blockchain. The proposed interoperability allows artwork trading participants on social media to maintain mutual trust and to conduct the contract transparently. Also, the proposed interoperability consists of an API provided by the social media developer or an open source API without having to modify existing social media. This study is expected to contribute to the growth of the art trading market on social media by complementing the art trading practices on social media.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.25-31
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• 2018

In recent years the privacy issue on social media is often being discussed. The purpose of this study is to explore the relationships among user gender, user group according to user activity level (highly active vs less active) and self-disclosure in social media. We collected a total of 180 million tweets issued by 13 million twitter users for 12 months and investigated attributes of tweet (user's profile, profile image, description, geographic information, URL) which are related to self-disclosure and boundary impermeability. The results show there are significant (p<0.001) interactions between user gender, user group and each attribute of tweet that are related to self-disclosure and show that the patterns of self-disclosure are different across attributes. The results also show that the mean self-disclosure scores and boundary impermeability of top 10% highly active users are significantly higher than other less active users for all genders.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.213-225
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• 2019

Privacy paradox is a paradoxical behavior that provides personal information even though you are concerned about privacy. Social media users are also often concerned about their personal information exposure. It is even reluctant to describe personal information in profile. However, some users describe their personal information in detail on their profile, provide it freely when others request it, or post their own personal information. The survey was conducted using Google Docs centered on Facebook users. Structural equation model analysis was used for hypothesis testing. As an independent variable, we use personal information infringement experiences. As a mediator, we use privacy indifference, privacy concern, and the relationship with the act of providing personal information. Social media users have become increasingly aware of the fact that they can not distinguish between the real world and online world by strengthening their image and enhancing their image in the process of strengthening ties, sharing lots of information and enjoying themselves through various relationships. Therefore, despite the high degree of privacy indifference and high degree of privacy concern, the phenomenon of privacy paradox is also present in social media.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.265-271
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• 2022

Social media is a form of communication based on the internet to share information through content and images. Their choice of profile images and type of image they post can be closely connected to their personality. The user posted images are designated as personality traits. The objective of this study is to predict five factor model personality dimensions from profile images by using deep learning and neural networks. Developed a deep learning framework-based neural network for personality prediction. The personality types of the Big Five Factor model can be quantified from user profile images. To measure the effectiveness, proposed two models using convolution Neural Networks to classify each personality of the user. Done performance analysis among two different models for efficiently predict personality traits from profile image. It was found that VGG-69 CNN models are best performing models for producing the classification accuracy of 91% to predict user personality traits.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.109-118
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• 2024

With the increasing number of social media users worldwide, cases of social media being abused to perpetrate various crimes are increasing. Specifically, drug distribution through social media is emerging as a serious social problem. Using social media channels, the curiosity of teenagers regarding drugs is stimulated through clever marketing. Further, social media easily facilitates drug purchases due to the high accessibility of drug sellers and consumers. Among various social media platforms, we focused on Instagram, which is the most used social media platform by young adults aged 19 to 24 years in South Korea. We collected four types of information, including profile photos, introductions, posts in the form of images, and posts in the form of texts on Instagram; then, we analyzed the similarity among each type of collected information. The profile photos and posts in the form of image were analyzed for similarity based on the SSIM(Structural Simplicity Index Measure), while introductions and posts in the form of text were analyzed for similarity using Jaccard and Cosine similarity techniques. Through the similarity analysis, the similarity among various accounts for each collected information type was measured, and accounts with similarity above the significance level were determined as the same drug sales account. By performing logistic regression analysis on the aforementioned information types, we confirmed that except posts in image form, profile photos, introductions, and posts in the text form were valid information for tracking the same drug sales account.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.98-105
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• 2013

Patterns for generating and consuming contents are various in these days from conventional broadcasting contents to UCC. There are many researches on developing recommendation engines based on user's profile for providing desired contents. In this paper we propose a contents recommendation system using not only user's profile but other's profiles in closed user group of the social network based on patterns for user's consuming contents. The proposed recommendation agent update user's profile using usage history and other's profiles related to the user in the closed user group.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1570-1594
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• 2017

Social network services have recently changed from environments for simply building connections among users to open platforms for generating and sharing various forms of information. Existing user reputation computation methods are inadequate for determining the trust in users on social media where explicit ratings are rare, because they determine the trust in users based on user profile, explicit relations, and explicit ratings. To solve this limitation of previous research, we propose a user reputation computation method suitable for the social media environment by incorporating implicit as well as explicit ratings. Reliable user reputation is estimated by identifying malicious information raters, modifying explicit ratings, and applying them to user reputation scores. The proposed method incorporates implicit ratings into user reputation estimation by differentiating positive and negative implicit ratings. Moreover, the method generates user reputation scores for individual categories to determine a given user's expertise, and incorporates the number of users who participated in rating to determine a given user's influence. This allows reputation scores to be generated also for users who have received no explicit ratings, and, thereby, is more suitable for social media. In addition, based on the user reputation scores, malicious information providers can be identified.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1154-1164
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• 2010

As an useful application in broadcasting services, the targeting service has been mainly studied to improve the service satisfaction and user usage in various media service environments based on user profile, preferences, and usage history. Targeting service is expanding its domain from broadcasting contents to interstitial contents and from fixed TV devices to mobile devices. Service data also include advertisement data, coupon, and information about media contents as well as simple broadcasting data. In this paper, the targeting data service is designed and implemented on articles, advertisement and broadcasting information on the basis of the user information. To adapt this to web-based media contents, information on user profile, preferences, and usage history is newly defined on the basis of the user metadata developed in TV-Anytime Forum and the user information defined in OpenSocial. The targeting data service is implemented to generate user preferences information and usage history pattern based on the similarity among user preference, contents information, and usage history. Based on performance evaluation, we prove that the proposed targeting data service is effectively applicable to web-based media contents as well as broadcasting service.

• Asian Journal for Public Opinion Research
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• v.1 no.4
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• pp.268-291
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• 2014

Social media is becoming more and more important in social movements. This study, adopting the web mining approach, attempts to investigate how social media, Facebook in particular, functioned in the "May 25 Protest" and the "May 27 Protest", two movements which broke out in Macao on 25 and 27 May 2014, respectively, against the Retirement Package Bill. In the two protests, Macao residents deployed Facebook to share information and motivated people's participation. Twelve events (181,106 people invited) and 36 groups/pages (41,266 members) related on Facebook were examined. Results showed that the information flow on Facebook fluctuated in accordance with the event development in reality. Multiple patterns of manifestation, such as video of adopted news or songs, designed profile (protest icon), original ironic pictures, self-organized clubs by undergraduates and white T-shirts as a symbol, among others, appeared online and interacted with offline actions. It was also found that social media assisted the information diffusion and provided persuasive reasons for netizens to join the movement. Social media helped to expand movement influence in providing a platform for diversified performances for actions taken in a protest, which could express and develop core and consistent movement repertoire.

• Korean Journal of Childcare and Education
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• v.17 no.3
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• pp.65-87
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• 2021

Objective: This study aimed to examine the effects of maternal monitoring, shared activities with children, maternal education-oriented behavior, and allowing children to own smart-phones on smart media usage patterns based on smart-phone usage time and purposes among elementary school children. Methods: The participants were 1,315 second-grade elementary school children from the 9th wave of PSKC. Latent profile analysis and the three-step estimation approach were used to examine the determinants of the latent profile and the effects of maternal parenting on the profile. Results: Four latent profiles were identified: 'High-level usage & Entertaining oriented,' 'Moderate-level usage & Social/entertaining oriented,' 'Moderate-level usage & Learning oriented,' and 'Low-level usage.' Additionally, results showed that each profile can be predicted by maternal monitoring, education-oriented behavior, and permitting children to own smart-phones. Conclusion/Implications: Our outcomes suggested that it would be necessary to understand the smart media usage patterns of elementary school children, considering both the amount of time spent with smart media and purposes of uses. Further, it is helpful for mothers to monitor children's daily activities, support their educational activities, and take the role of gatekeeper for smart media as a way of appropriate guidance for their children's use of smart media.