• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2011.11a
• /
• pp.52-53
• /
• 2011

• Journal of KIISE
• /
• v.41 no.12
• /
• pp.1066-1074
• /
• 2014

In this paper, we present a visual analytics system that uses serial-correlation to detect an abnormal event in spatio-temporal data. Our approach extracts the topic-model from spatio-temporal tweets and then filters the abnormal event candidates using a seasonal-trend decomposition procedure based on Loess smoothing (STL). We re-extract the topic from the candidates, and then, we apply STL to the second candidate. Finally, we analyze the serial-correlation between the first candidates and the second candidate in order to detect abnormal events. We have used a visual analytic approach to detect the abnormal events, and therefore, the users can intuitively analyze abnormal event trends and cyclical patterns. For the case study, we have verified our visual analytics system by analyzing information related to two different events: the 'Gyeongju Mauna Resort collapse' and the 'Jindo-ferry sinking'.

• The Journal of the Korea Contents Association
• /
• v.13 no.3
• /
• pp.131-140
• /
• 2013

Assuming that roles of traditional mass media are also shown in Twitter services, the study aims at exploring Twitter users' motives and rationales in re-tweet behavior. Based on the laddering interview method, the study gathers data on (1) message attributes (what kinds of messages do you re-tweet?); (2) consequences (what kinds of consequences are you expecting when you re-tweet?); and (3) values (what are the ultimate values in your re-tweet behavior?). The most repetitive value occurring in participants' retweet was feeling "sympathy" and "sharing" rationales. For such rationales, participants oftentimes utilize messages with "agenda" and "information" that are relative to themselves. Messages with "helping" to help others also frequently showed up in their retweet rationales. Known as liberalists' rationales, "communal consciousness", and "calling for others' action" are also shown, but not as frequent as "feeling sympathy and sharing. A total of 48 items from the analyses were used in a subsequent study as variables to identify factors (dimensions) of retweet motivation.

• Journal of Korea Multimedia Society
• /
• v.17 no.1
• /
• pp.43-51
• /
• 2014

Social Network Service has the sufficient potential can be widely and effectively used for various fields of society because of convenient accessibility and definite user opinion. Above all Twitter has characteristics of simple and open network formation between users and remarkable real-time diffusion. However, real analysis is accompanied by many difficulties because of semantic analysis in 140-characters, the limitation of Korea natural language processing and the technical problem of Twitter is own restriction. This thesis paid its attention to human's political attitudes showing permanence and assumed that if applying it to the analytic design, it would contribute to the increase of precision and showed it through the experiment. As a result of experiment with Tweet corpus gathered during the election of national assemblymen on 11st April 2012, it could be known to be considerably similar compared to actual election result. The precision of 75.4% and recall of 34.8% was shown in case of individual Tweet analysis. On the other hand, the performance improvement of approximately 8% and 5% was shown in by-timeline political attitude analysis of user.

• Journal of the Korean Society for information Management
• /
• v.33 no.2
• /
• pp.135-156
• /
• 2016

Recently, as the importance of user-oriented archives management is becoming increasingly, government archives try to serve interactive services using social network service (SNS) beyond one-way approaches. This study aims to analyze usage of government archives service in social media and examine users' interestedness. We especially select "National Archives of Korea" and "Presidential Archives" as target government archives and collect tweets from 2010 to 15th April 2016. Our study adopts informetric approaches and social media analysis including buzz analysis, time series analysis. We differentiate between the tweet collection posted by government archives themselves and the other collection generated by general users. Furthermore we conduct correlation analysis of tweet and social issues and propose application plan for government archives services in social media environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.05a
• /
• pp.252-255
• /
• 2011

Growing demand for smart phones and data communication diminishes the constraints of Twitter and Facebook than a smartphone has become a subject of interest. On the other hand facebook users in their relationships to obtain the consent of the other, twitter is a relatively simple procedure for the information ripple effect is excellent. Twitter is beyond a simple social networking services(SNS) located in one of the popular media and powerful have the upper retweet. Retweet to the top of his sympathy with the ability th send tweets to their subscriber information can spread quickly. In this paper, we propose the smart retweet that system actively extend the existing retweet. In order to realize the smart retweet and additional criteria for determining the destination of the information is required. Based on tweet generated regional or an local information mentioned to tweet, to determine the destination. Smart retweet of the speed and scope of information transmission through the scale is expected.

• The Journal of the Korea Contents Association
• /
• v.16 no.4
• /
• pp.434-441
• /
• 2016

Using bigdata analysis procedures, the present study sought to review and explore the various aspects of self-disclosure and boundary impermeability of worldwide twitter users. A total of 415 million tweets issued by 54 million users were collected during 6 months and the users of top 10 languages were investigated. And the effect of languages of twitter users on the boundary impermeability, disclosure rate of user profile, profile image, geographical information, URL in profile and user description were analyzed in this study. The results showed that the boundary impermeability and all the self-disclosure rates of twitter users (profile, profile image, geographical information, URL in profile, user description) were significantly (p<0.001) different among language groups of users. The self-disclosure rates and the average points of Portuguese, Indonesian and Spanish users were higher than those of Arabic, Japanese, Turkish and Korean users. The results also showed a positive relationship between boundary impermeability and the number of tweets (including retweets) issued by each users.

• Journal of Korea Multimedia Society
• /
• v.15 no.7
• /
• pp.910-919
• /
• 2012

We have observed huge success in social network services like Facebook and Twitter, and many researchers have done their analysis on these services. As massive data observed by users is produced on Twitter, many researchers have been conducting research to detect an event on Twitter. Some of them developed a system to detect the earthquakes or to find the local festivals. However, they did not consider the credibility of location information on Twitter although their systems were using the location information. In this paper, we analyze the credibility of the profile location and the correlation between the spatial attributes on Twitter as the preliminary research of the event detection system on Twitter. We analyzed 0.5 million Twitter users in Korea and 2.8 million users around the world. 49.73% of the users in Korea and 90.64% of the users in the world posted tweets in their profile locations. This paper will be helpful to understand the credibility of the spatial attributes on Twitter when the researchers develop an application using them.

• Journal of Digital Convergence
• /
• v.14 no.3
• /
• pp.165-170
• /
• 2016

The purpose of this study was to explore the differences in sentiment on social networking sites among six languages (English, German, Russian, Spanish, Turkish and Dutch). A total of 204 million tweets were collected using Streaming API. Subjective/objective ratio, sentiment strength, positive/negative ratio, number of retweets and boundary impermeability were analyzed with SentiStrength to estimate the trends of emotional expression via Twitter. The results showed that subjective/objective ratio and the positive/negative ratio of tweets were significantly different by languages (p<0.001). And, there were significant effects of language on sentiment strength, boundary impermeability and the number of retweets (p<0.001). The results also indicate that the cross-cultural, language differences should be taken into account in sentiment analysis on SNS.

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