• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.188-202
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• 2014

This major purpose of this study is to examine factors influencing the attitude toward News Feed advertising in Facebook. For this purpose, this study posited seven determinants including informativeness, entertainment, irritation, trust, individualization, incentive and privacy concern, which can have influences on the attitude toward News Feed Advertising. and this research tests the relationships between these seven determinants and the attitude toward News Feed Advertising. An online survey was administrated to collect data and hierarchical regression analyses were employed for data analysis. The results showed that infortainment as a new combined factor of informativeness and entertainment, trust, individualization have significantly positive influences on the attitude toward News Feed advertising in Facebook. It was also shown that the moderating effect of involvement on the relationship between irritation and the attitude. The results in this study implied that it is needed to reinforce the attributes of advertising including infortainment, trust and individualization to boost the effects of News Feed advertising in Facebook on consumers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1015-1021
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• 2020

Mobile news users want news articles without advertising, meanwhile the news providers require advertisement displays in several types to attain advertising revenue. In this paper, we classified the types of advertisements on mobile news articles into fixed article type which is fixed on some areas of articles, fixed screen type which is fixed on mobile screens, and a combination type of them. In addition, we proposed a smart solution based on overlapping method which effectively organize advertisements to not distract the readers. The proposed method is similar to fixed article type and overlapping technique of advertisements on news article's photo or virtual area. The performance evaluation result shows that the proposed method provides more spaces for news articles effectively than the existing methods. Although only some areas of advertisements may be blocked according to the number or size of advertisements, the effect is not critical.

• Journal of Korea Multimedia Society
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• v.17 no.2
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• pp.218-225
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• 2014

The marketing which uses SNS, which has the most biggest growth since appearance of Facebook, is proved to be effective, then many companies make variable attempts of marketing by using Facebook. This paper presents the method of marketing using videos, that has a major part in Facebook, and the method to raise their ratings. By using the video play button it registers information of the videos in Facebook then shares them to other people in real-time through inner News Feed. Therefore, we can maximize effect of marketing through viral marketing to use other users responses.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.937-940
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• 2017

본 연구는 유저 크리에이티브 지식 매체를 생성함에 있어 기존 일방적 전달 방식에서 탈피하여 자신이 가지고 있는 정보를 다수의 사람과 공유 할 수 있는 3세대 다방향(Mash-Up) 교육에 관한 연구하여 SNS와 클라우드 요소를 통해 공유할 수 있는 플랫폼을 개발하는 방안을 제안하고 있다. 본 연구는 1)LIVE_BOARD 2)TIMELINE 3)NEWS FEED 4)PLANNER로 나뉜다. Live_Board의 실시간 스트리밍을 활용하여 영상 이미지기반 의사소통을 지원하고, SNS적 요소인 TimeLine, News Feed를 통해 다른 사용자들과 정보 공유를 할 수 있고, Planner를 통해 개인 스케줄 관리를 할 수 있는 플랫폼이다.

• The Korean Journal of Financial Management
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• v.14 no.1
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• pp.141-169
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• 1997

본 논문은 시장개설 초기 4개월간의 주가지수 선물수익률과 기초자산인 현물(KOSPI 200) 수익률간의 선도-지연효과를 두 개의 모형을 이용하여 실증검증하였다. 첫 번째 모형은 설명 변수로 선물수익률의 시차변수를 사용하고 종속변수로 현물수익률을 사용했다. 두 번째 모형은 설명변수로 선물수익률의 시차변수를 사용하는 것은 첫 번째 모형과 같으나 종속변수로 ARMA모형에서 구한 현물수익률의 오차항(return innovations)을 사용하였다. 또, 여러 시장조건에서 현물수익률과 선물수익률사이의 선도-지연효과가 특정한 양상을 보이는가를 분석하였다. 좋은 정보와 나쁜 정보, 거래량이 많은 경우와 적은 경우, 변동성이 높은 경우와 낮은 경우로 나누어서 선도-지연효과를 살펴보았다. 실증검증의 결과 KOSPI 200 현물수익률은 ARMA(2,3) 모형이 적합하며 선물이 현물을 10분 이내로 선도한다. 하지만 그 관계는 일방적인 것이 아니어서 15분후에는 현물이 선물을 선도하는 피드백(feed-back) 현상이 나타났다. 좋은 정보(good news)에서는 선물이 현물을 5분정도 선도하고 나쁜 정보(bad news)하에서는 선물 선도현상이 약해진다. 보통 정보(morderate news)하에서는 현물이 선물을 10분내로 선도한다. 거래량이 많은 경우와 변동성이 높은 경우에는 선물이 현물을 선도하는 것이 뚜렷하나 거래량이 적은 경우와 변동성이 낮은 경우에는 선물과 현물간에는 특정한 선도-지연현상이 나타나지 않는다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.960-966
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• 2012

It is prevalent to gather the location information from GPS, WiFi and etc, and therefore LBSNS (Location-Based SNS) has increased rapidly (such as location-augmented Twitter services). The message created from LBSNS include the specific area of interests which the message is created in or mentions. It is easy to propagate the location-based information of LBSNS by adapting the retweet function which is efficient way to propagate the message in tweeter. In this paper, we have defined the smart retweet as a automatic retweet function for efficient propagating the messages which is geo-tagging the location of interests. We have designed the smart retweet system based on the tweeter system. The user could specify the area of interests and build the social networking among the users which have interested in common area. The smart retweet system have been implemented by mesh-up services based on Open-API of trweeter and google map. It is expected that the smart retweet service proposed in this paper makes easy sharing of the location-based interesting information.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.10
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• pp.251-258
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• 2018

Ransomware, a malicious software that requires a ransom by encrypting a file, is becoming more threatening with its rapid propagation and intelligence. Rapid detection and risk analysis are required, but real-time analysis and reporting are lacking. In this paper, we propose a ransomware infection detection system using social big data mining technology to enable real-time analysis. The system analyzes the twitter stream in real time and crawls tweets with keywords related to ransomware. It also extracts keywords related to ransomware by crawling the news server through the news feed parser and extracts news or statistical data on the servers of the security company or search engine. The collected data is analyzed by data mining algorithms. By comparing the number of related tweets, google trends (statistical information), and articles related wannacry and locky ransomware infection spreading in 2017, we show that our system has the possibility of ransomware infection detection using tweets. Moreover, the performance of proposed system is shown through entropy and chi-square analysis.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.115-136
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• 2007

In this study, we investigate the possibility of deploying a recently emerging Internet-based technology, called Web log or Blog, to address the problems of knowledge transfer and sharing, particularly in the case of tacit knowledge. We examined the use practice of four blogs and then identified several properties relevant to knowledge transfer and sharing. They include the specific style of blog format, content ownership attribution, posted article organization, communication tools and method, news feed function, and various links from/to outside websites. These features were argued to facilitate knowledge transfer and sharing. In particular, we discussed a great deal about the structure of comments and links as tools for collaboration and idea sharing, which enables the knowledge conversion processes (socialization, externalization, combination, and internalization), We then provide several guidelines to develop blogs as a knowledge management tool.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1476-1478
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• 2013

최근 페이스북(Facebook), 트위터(Twitter) 등의 SNS(Social Network Service)의 사용자가 급격하게 증가하고 있다. SNS가 발달하면서 언제 어디서나 쉽게 자신의 위치, 현재의 감정들을 온라인상에서 공유한다. 이에 따라 사람의 감정을 표현하는 단어 100여개를 7가지 감정(기쁨, 흥미, 슬픔, 분노, 놀람, 지루함, 통증)으로 분류하였으며[1]. 이를 분석하기 위한 감정 표현 분석기 모듈을 설계하였다. 설계한 모듈을 사용하여 페이스북의 사용자 뉴스피드(News-Feed)를 분석하여 사용자의 성향을 분석하였다.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.166-171
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• 2023

The Stock price analysis is an increasing concern in a financial time series. The purpose of the study is to analyze the price parameters of date, high, low, and news feed about the stock exchange price. Long short term memory (LSTM) is a cutting-edge technology used for predicting the data based on time series. LSTM performs well in executing large sequence of data. This paper presents the Long Short Term Memory Model has used to analyze the stock price ranges of 10 days and 20 days by exponential moving average. The proposed approach gives better performance using technical indicators of stock price with an accuracy of 82.6% and cross entropy of 71%.