• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.137-147
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• 2013

The purpose of this study is to examine what variables influence on tweet credibility and attitude toward tweet. For this, the present research used the tweet content(information/opinion), tweet function(without URL and RT/URL/RT) and involvement(low/hight) as independent variables and applied a triangular research design which are in-depth interview, survey and computer usability testing software. Main findings are as follows. First, the participants read tweets listed in order regardless of tweet content, function and involvement. Second, there was a significant main effect of the tweet content on the tweet credibility and an interaction effect of those three independent variables on the attitude toward tweet. Finally, the in-depth interview showed that information is perceived to be more credible than opinion and URL>RT>just information or opinion are listed in order on the tweet credibility.

• ETRI Journal
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• v.36 no.3
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• pp.418-428
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• 2014

In social network services, such as Facebook, Google+, Twitter, and certain postings attract more people than others. In this paper, we propose a novel method for predicting the lifespan and retweet times of tweets, the latter being a proxy for measuring the popularity of a tweet. We extract information from retweet graphs, such as posting times; and social, local, and content features, so as to construct prediction knowledge bases. Tweets with a similar topic, retweet pattern, and properties are sequentially extracted from the knowledge base and then used to make a prediction. To evaluate the performance of our model, we collected tweets on Twitter from June 2012 to October 2012. We compared our model with conventional models according to the prediction goal. For the lifespan prediction of a tweet, our model can reduce the time tolerance of a tweet lifespan by about four hours, compared with conventional models. In terms of prediction of the retweet times, our model achieved a significantly outstanding precision of about 50%, which is much higher than two of the conventional models showing a precision of around 30% and 20%, respectively.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.241-262
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• 2017

This study aims to identify and analyze the Twitter use of domestic public libraries. In order to identify the detailed patterns of Twitter use in library and information services, a content analysis was conducted for the 3,038 tweet data from the top 14 public libraries' accounts on Twitter use. Inductive approach was adopted to develop a coding scheme and open coding was conducted with the entire tweet. Additionally, correspondence analysis was conducted for the result of content analysis to identify how library accounts correspond to specific types. As a result, 3 main categories and 9 sub-categories of public libraries' Twitter use were developed. And the 37 detailed patterns of public libraries' use of Twitter were identified. The identified patterns can provide the libraries interested in Twitter use with guidelines.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.905-907
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• 2014

Twitter is the special place that people in the world can freely share their information and opinion. There are tries to utilize a vast amount of information made from twitter. The study on classification of tweets by subject is actively conducted. Twitter is a service for sharing information with short 140-characters text message. The short message including brief content makes extracting a variety of information hard. In the paper, we suggests the method to classify tweet by subject. The method uses both tweet and subject features. In order to conduct experiments to verify the proposed method, we collected 10,000 tweet messages with the Twitter API. Through the experimental results, we will show that the performance of our proposed method is better than those of previous methods.

• Journal of KIISE
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• v.41 no.12
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• pp.1136-1144
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• 2014

Twitter is a social network service that generates about 140 million contents a day. Contents of Twitter contain a variety of information and many researchers research those in various fields. In this research, we propose a method for evaluating the importance of content based on characteristics of Twitter. We have found that number of follower means user's popularity and Re-tweet that means the popularity of content. We perform experiments about proposed method using real Twitter data for proving effectiveness of proposed method. Also, we found information providers in Twitter are public user who represent a company or a representative of a specific group.

• The Korean Journal of Archival Studies
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• no.50
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• pp.139-175
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• 2016

This study is a content analysis on the National Archives of Korea as reflected in tweets produced between 2014 and 2015. The study thus collected all tweets that used the key word 'National Archives of Korea' from 2014 and 2015. The contents of the tweets, including their category and issues mention, were then analyzed. The results of the analysis were as follows. First, the analysis showed that the collected archives of the National Archives had increased their volume in over two years, which have a similar type and pattern in their content. Second, the tweets produced by the public reflects more current political and social issues rather than archival service.

• Journal of Korean Library and Information Science Society
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• v.46 no.1
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• pp.115-133
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• 2015

This study investigates the contents of twitters serviced by metropolitans and citizens' questions to propose improvements. Using content analysis as a research method, this study recorded and analyzed all the tweets of six metropolitans (Seoul, Busan, Daegu, Incheon, Daejeon, Gwangju) for three months. As the results, the frequency analysis of tweets revealed that Busan posted more tweets than other cities, and Seoul posted the highest number of tweet using URL link. The results of content analysis showed that the most frequently provided information from tweeters was about convenience of citizens living. Tweets using URL link were focused on information about citizen living, prize contest, and service announcement. Citizens had a request for information about their life and traffic. For public information service using tweeter in the future, this study provided several important suggestions.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.240-245
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• 2016

In this study, comments on restaurants, movies, and mobile devices, as well as tweet messages regardless of specific domains were analyzed for sentimental information content. We proposed a system for extraction of objects (or aspects) and opinion words from each sentence and the subsequent evaluation. For the sentiment analysis, we conducted a comparative evaluation between the Structural SVM algorithm and the Latent Structural SVM. As a result, the latter showed better performance and was able to extract objects/aspects and opinion words using VP/NP analyzed by the dependency parser tree. Lastly, we also developed and evaluated the sentiment detector model for use in practical services.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.928-931
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• 2014

The detection of human behavior from social media revolutionized health, business, criminal and political prediction. Significance of it, in incentive transformation of public opinion had already proven for developed countries in improving democratic process of elections. In $3^{rd}$ World countries, voters poll votes for personal interests being unaware of party manifesto or national interest. These issues can be addressed by social media, resulting as ongoing process of improvement for presently adopted electoral procedures. On the optimistic side, people of such countries applied social media to garner support and campaign for political parties in General Elections. Political leaders, parties, and people empowered themselves with social media, in disseminating party's agenda and advocacy of party's ideology on social media without much campaigning cost. To study effectiveness of social media inferred from individual's political behavior, large scale analysis, sentiment detection & tweet classification was done in order to classify, predict and forecast election results. The experimental results depicts that social media content can be used as an effective indicator for capturing political behaviors of different parties positive, negative and neutral behavior of the party followers as well as party campaign impact can be predicted from the analysis.

• Korean journal of communication and information
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• v.59
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• pp.138-161
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• 2012

This study is designed to explore the function of Twitter as a campaign platform during election campaign. For exploring the function of Twitter the form of tweet, the type of information on tweet and the way of opinion expression via Twitter were discussed by content analysis. This study finds, first, that, netizens express their opoinion of candidates without foundation and with emotional reactions. Second, they showed somewhat conflictive reactions according to their supporting candidates. This study conceptualized various kinds of public as 'blindly support public,' and 'blindly opposition public' in case of Park's supporters, 'rational support public,' and 'critical opposition public' in case of Na's supporters. Third, Park's supporters debated Na candidate's attitude of debate and her appearance blindly without foundation. Na's supporters argued Park's attitude of debate and his ignorance of Seoul Metropolitan government's policy blindly without foundation. Finally, this study discussed the relationship between the political discourse according to netizens' supporting via Twitter and the results of election. Park whose supporters attacked the opposing candidate by blaming her appearance and her attitude of debate won the election. Na didn't overcome her negative images. For her Twitter functioned as a media which is spreading negative factors about her. In conclusion, Twitter as a campaign platform during election times plays a key role in discussing candidates. However, netizens need to express their opinions with foundation and the candidates have to consider negative issue management. This study highlights the importance of peripheral factors which have a decisive effect on the results of election. The results of this study is useful for building political campaign strategy by candidates.