• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.2
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• pp.57-78
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• 2017

SNS is a useful tool to quickly deliver information in an emergency given their speed and expandability. Especially, SNS in the event of a disaster or an accident can offer on-site, accurate and detailed updates about essential information such as the safety of victims and the development of the situation, served as a valuable complement to the conventional media. This study aims to perform a comparative analysis on how social media are currently used by emergency management authorities in South Korea and other countries. Based on the results, this study proposed more effective ways to exploit SNS and improve efficiency of disaster management. To accomplish the goals, this study collected tweet information from various sources including the FEMA of the U. S., the FDMA and the Central Disaster Council of Japan, and the MPSS of Korea. The collected tweet information was analyzed by feedback, time series, and information types. The feedback analysis aims to quantify the number of monthly user feedback in order to assess user satisfaction about the tweet information. The time series analysis identifies the number of tweet information, feedback index and keywords by country for certain duration, examining why certain messages showed high feedback indices and what kind of contents should be offered by the authorities. Finally, the analysis of information type reviews the type of information contained in the tweet information that drew users' attention to identify the information type in which the authorities should deliver information to users. Based on these analyses, this study proposed improvement methods to use Tweeter in MPSS.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1286-1295
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• 2014

This paper suggests the way that it could improve the reliability about preference of user's feedback by adding weighting factor on sentiment analysis, and efficiently make a sentiment analysis of users' emotional perspective on the big data massively generated on twitter. To solve errors on earlier studies, this paper has improved recall and precision of sensibility determination by using sensibility dictionary subdivided sentiment polarity based on the level of sensibility and given impotance to sensibility determination by populating slang, new words, emoticons and idiomatic expressions not in the system dictionary. It has considered the context through conjunctive adverbs fixed in korean characteristics which are free to the word order. It also recognize sensibility words such as TF(Term Frequency), RT(Retweet), Follower which are weighting factors of preference and has increased reliability of preference analysis considering weight on 'a very emotional tweet', 'a recognised tweet from users' and 'a tweeter influencer'

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1710-1712
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• 2012

최근 Twitter를 비롯한 소셜 네트워크 서비스의 급속한 확산으로 인해, 많은 수의 SNS 메시지가 실시간으로 생성되고 있다. 이러한 SNS상에서의 단문 글들을 실시간으로 분석하여 최신의 트렌드를 추출해 낼 수 있다면, 사용자에게 유용한 정보를 제공하는 것이 가능하다. 본 논문에서는 다량의 Tweet글들에 대한 실시간 분석을 바탕으로 트렌드를 추출하고 연관된 키워드를 제공하는 기법을 제안한다. 제안하는 기법은 실시간으로 생성되는 Tweet내에서 영어의 언어적 특성을 활용하여 최근 이슈화된 트렌드 키워드를 추출해낸다. 또한, Tweet 내에서 각 트렌드 키워드간 관계를 분석하여 연관 키워드를 제공하며, 동시에 Wikipedia와 Google에서의 검색을 통하여 다른 형태의 연관 키워드도 추출한다. 이 모든 과정은 제안된 트렌드 추출 알고리즘을 통해 실시간으로 제공된다. 제안된 기법을 바탕으로 시스템을 구현하고 다양한 실험을 통하여 키워드의 유효성 및 처리 속도 면에서 시스템의 성능을 평가한다.

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

• Spatial Information Research
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• v.22 no.3
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• pp.1-8
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• 2014

While SNS services such as Twitter or Facebook are rapidly growing, research for the SNS analysis has been concerned. Especially, twitter reacts to social issues in real-time so that it is used to get useful experimental data for researchers of social science or information retrieval. However, it is still lack of research on the methodology to collect data. Therefore, this paper suggests the tweet acquisition system by considering tendency of twitter user oriented location-based event and political social event. First the system acquires tweets including information of location and keyword about event and secure IDs for acquisition of political social event. Then we plan ID-analyzer to classify the tendency of users. In addition for measuring reliability of ID-analyzer, it acquires and analyzes the tweet by using high-ranked ID. In analyses result, top-ranked ID shows 88.8% reliability, 2nd-ranked ID shows 76.05% and ID-analyzer shows 77.5%, it shortens collection time by using minority ID.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.267-276
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• 2017

Damages have occurred in various fields such as agriculture, industry, and citizen's health due to the yellow dust. Therefore, it is urgent to take measures against it. In this regard, this study collected data of yellow dust over 11 days on a basis of Feb. 23. 2015 when yellow dust was the greatest after 2009, issue words analysis and recomposed health related tweet data. After testing the significance of yellow dust related diseases by association rule analysis with diseases, it obtained the study results as follows: As a result of significance test for the patients with rhinitis, asthma and conjunctivitis by acquiring the condition data of patients from the Health Insurance Review & Assessment Service, conjunctivitis appeared to be significant in 13 cities for 16 cities at 5% significance probability, while asthma and rhinitis showed a significance in 3 and 6 areas. As described above, it is possible to obtain information about citizens' health from SNS data, such as Tweet data and it is judged that these data will provide useful information for establishing measures of citizens' health care.

• Journal of the Korean association of regional geographers
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• v.23 no.2
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• pp.376-387
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• 2017

This paper attempts to analyze the geographical characters of Twitter data and presents analysis potentials for social network analysis in geography. First, this paper suggests a methodology for a topic modeling-based approach in order to identify the geographical characteristics of tweets, including an analysis flow of Twitter data sets, tweet data collection and conversion, textural pre-processing and structural analysis, topic discovery, and interpretation of tweets' topics. GPS coordinates referencing tweets(geotweets) were extracted among sampled Twitter data sets because it contains the tweet place where it was created. This paper identifies a correlated relationship between some specific topics and local places in Jeju. This correlation is closely associated with some place names and local sites in Jeju Island. We assume it is the intention of tweeters to record their tweet places and to share and retweet with other tweeters in some cases. A surface density map shows the hotspots of tweets, detecting around some specific places and sites such as Jeju airport, sightseeing sites, and local places in Jeju Island. The hotspots show similar patterns of the floating population of Jeju, especially the thirty-year age group. In addition, a topic modeling algorithm is applied for the geographical topic discovery and comparison of the spatial patterns of tweets. Finally, this empirical analysis presents that Twitter data, as social network data, provide geographical significance, with topic modeling approach being useful in analyzing the textural features reflecting the geographical characteristics in large data sets of tweets.

• Spatial Information Research
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• v.23 no.5
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• pp.1-7
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• 2015

Twitter has the fast propagation and diffusion of information compare to other SNS. Therefore, many researches about detecting real-time event using twitter are progressing. Twitter real-time event detecting system assumes every twitter user as a sensor and analyzes their written tweet in order to detect the event. Researches that are related to this twitter have already obtained good results but confronted the limits because of some problems. Especially, many existing researches are using the method that can trace an event location by using GPS coordinate. However, it can be suggested a definite limitation through the present user's skeptical responses about making personal location information public. Therefore, this paper suggests the method that traces the location information in tweet contents text without using the provided location information from twitter. Associated words were grouped by using the keyword that extracted in tweet contents text. The place that the events have occurred and whether the events have surely occurred are detected by this experiment using this algorithm. Furthermore, this experiment demonstrated the necessity of the suggested methods by showing faster detection compare to the other existing media.