• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.107-130
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• 2012

In Twitter, a user can post a message below 140 characters on his/her account, and can also repost a message of other users who the user follows. The message posted by the user in turn can be seen and reposted by other users who follow the user, which is called Re-tweet (RT). While some messages spread widely, other messages have relatively less or no RT. What factors cause these quantity variances of RT originated from original messages? How can the messages become influential in online social networks? As an effort to answer the above questions, we focused on information vividness, message characteristics, and originator characteristics. In perspective of managerial implication, we expect that the findings of this paper will provide corporations with helpful insight on the Word-of-Mouth (WOM) effect for efficient and effective advertisements and communications when they send a message of new products or services through Social Network Services. In perspective of academic implication, we identify the effect of contents of a message on WOM, which has been dealt with by few social network researches.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.57-69
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• 2020

As more people share their opinions in online communities, such as Internet portals and social networking services, more opinions are manipulated for the benefit of particular individuals and groups. In particular, when manipulations occur for political purposes, they influence election results as well as government policies and the quality of life. This type of manipulation has targeted the general public, and their analysis and detection has also focused on such manipulation. However, to more efficiently spread propaganda, recent manipulations have targeted common interest groups(e.g., a group of those interested in real estate) and propagated information whose content and style are customized to those groups. This work characterizes such manipulations on common interest groups and proposes method to detect manipulations. To this end, we collected and analyzed opinions posted on 10 common interest groups before and after an election. As a result, we found that manipulations on common interest groups indeed occurred and were gradually increasing toward the election date. We also proposed a detection system that examines individual opinions, their authors, and their collaborators. Using the collected opinions, we demonstrated that the proposed system can accurately classify more than 90% of manipulated opinions and that many of these opinions were posted by multiple collaborators. We believe that regular audits of opinions using the proposed system can quickly isolate manipulations and decrease their impact. Moreover, the proposed features can be used to identify manipulations in domains other than politics.

• 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.

• Smart Media Journal
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• v.5 no.3
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• pp.54-61
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• 2016

According to many smart devices are development, SNS(Social Network Service) users are getting higher that is possible for real-time communicating, information sharing without limitations in distance and space. Nowadays, SNS users that based on communication and relationships, are getting uses SNS for information sharing. In this paper, we used the SNS posts for users to extract the category and information provider, how to following of recommend method. Particularly, this paper focuses on classifying the words in the text of the posts and measures the frequency using Inception-v3 model, which is one of the machine learning technique -CNN(Convolutional Neural Network) we classified image word. By classifying the category of a word in a text and image, that based on DMOZ to build the information provider DB. Comparing user categories classified in categories and posts from information provider DB. If the category is matched by measuring the degree of similarity to the information providers is classified in the category, we suggest that how to recommend method of the most similar information providers account.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.649-651
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• 2021

In recent years, O2O services for real estate sales are widely distributed in web platforms and apps. This allows sellers, buyers, and real estate brokers to quickly and conveniently conduct real estate sales and charter contracts. However, in the O2O-based real estate sales information system, it wastes time and money for real estate buyers due to the posting of fake information, partial correction of the sales information, and intentional non-posting of the sales information. Therefore, we propose a method of detecting the false or not of real estate property information that can occur on the web platform, and design and implement a proposal system for this. To this end, we propose a method of detecting personal identity and property information based on DID, a distributed identity authentication protocol. The false real estate sales information detection system proposed by us can determine the existence of real estate sales information, partially correct the false sales information, or prove whether or not intentionally unpublished in three steps.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.311-313
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• 2003

본 논문은 , 내용 은닉 서명［1］과 시간-잠금 퍼즐［2］을 이용해서 익명성을 보장하는 ［3］의 공모자 추적 스킴이 사실상 익명성을 갖지 않는다는 것에 대해서 보인다. 그 다음, 신뢰 기관을 이용하여 익명성을 보장하는 두개의 스킴을 제시한다. 첫 번째 스킴은 게시판과 ［4］의 영지식에서의 증명을 이용해서 ［3］에 제시된 스킴을 변형시켜 익명성을 보장한다. 두 번째 스킴은 ［5］의 비대칭 공모자 추적 스킴을 이용해서 익명성을 보장하는 공개키 공모자 추적 스킴을 제공한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.245-249
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• 2000

현재 웹 기반 가상 교육 시스템은 가상 강의실에서 학습자들이 볼 수 잇는 강의내용은 HTML 형식의 문서이다. 이는 HTML문서의 한계 때문에 학습자들은 강의 컨텐츠를 읽어 단순히 강의내용을 이해하는 수준으로만 학습이 가능하다. 본 논문에서는 최근 인터넷상에서 표준 공통포맷으로 대두되고 있는 XML을 이용하여 게시될 강의내용을 구조화하여 효율적인 학습이 가능하도록 XML기반의 강의 컨텐츠 구조를 제안하였다. XML기반의 강의 컨텐츠는 학습자들의 요구에 따른 유연성을 제공할 뿐만아니라 내용을 기반으로 한 분석이 가능하여 데이터 중심의 구조화가 가능하므로 처리 응용에도 의미정보로 저장하여 다양하고 효과적인 가상 강의실을 지원할 수 있는 가상교육시스템구축이 가능하다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.133-135
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• 2007

본 연구는 동남아 각국에서 시행되고 있는 레저 스쿠버 잠수 인증 제도에 대한 자료를 수집하고, 잠수 현황 및 인중 현황을 비교하였다. 자료 수집을 위해 인터넷에 게시된 내용을 많이 활용하였고, 관련 문헌을 조사하였으며, 자료 보완을 위해 잠수 협회 관계자, 2007년 동남아 각국의 DIVE EXPO 에 참가한 동남아 각국의 관공홍보 정부 관계자, 잠수 리조트 운영자 및 강사들과 폭 넓은 인터뷰를 하였다. 논문에는 인증 제도에 대한 이해를 돕기 위해 스쿠버 잠수 인증 단체의 설립 역사를 간략히 소개하였고, 스쿠버 인증과 국채 표준의 관계에 대해서도 언급하였다.

• Knowledge Management Research
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• v.23 no.2
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• pp.211-228
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• 2022

As social media marketing becomes prevalent, it is necessary to understand the administrative role of managers in promoting user engagement. However, little is known about how community managers enhance user engagement in social media. In this research, we study how managers can boost online user participation, including clicking likes and writing comments. Using the SUR (Seemingly Unrelated Regression) model, we find out that the active participation of managers increases user engagement of both passive (likes) and active (comments) ones. In addition, we find that the number of emotional words included in posts has a positive effect on the passive engagement whereas it negatively affects the active engagement. Lastly, the congruency between posts and comments positively affects users' passive engagement. This study contributes to prior literature related to online community management and text analyses. Furthermore, our findings offer managerial insights for practitioners and social media managers to further facilitate user engagement.

• Korean Association of Arts Management
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• no.57
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• pp.59-84
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• 2021

This study examined the structure of YouTube video network and the factors for the diffusion of Chinese creator's videos through the case of famous Chinese creator Fengtimo. There is few interest to the diffusion of Chinese contents among Korean researchers, while they have been studied the consumption of Hallyu(Korean wave) contents overseas. Using the data that YouTube Data API offers, this study analysed the video network that the comments of which are same users with NodeXL tools and the regression model with JASP tools. The study found that there are three groups of the YouTube channels of that network. They are domestic official accounts of Fengtimo, foreign officail accounts of Fengtimo and individual creators' accounts. The official accounts share the videos of Fengtimo's songs and entertainment contents for the fans, where the individual creators share their own meme videos(UGC). The significant factors for the diffusion in the YouTube video network are comments, likes, out-degree, dislikes, in-degree and betweenness centrality. There are significant difference between official channel and indivisual groups on the views. And degree and betweenness centrality have mediating effect. It is necessary to conduct more research on that subject with many other cases if we want to get to know the generalized explanation.