• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.345-348
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• 2008

본 연구는 체계적인 문헌연구를 통해 웹2.0의 사용이익과 도입요인을 분석하였다. 전자저널 검색결과 259편의 문헌 중에서 도입 기업사례 및 사용요인 관련 연구 10편을 선별하였다. 선택된 논문을 웹2.0기술의 사용이익과 성과, 웹2.0기술 수용요인, 블로그 사용자 행동 및 동기의 주제로 나누어 구분하였다. 이를 통해 본 논문에서는 웹2.0기술에 대한 실제 사용이익을 정보이익, 사회적 이익, 업무관련이익, 지식관련이익으로 제안하였다. 수용요인에 대한 연구결과로는 웹2.0 특성변수를 반영한 요인으로 지각된 참여성과 동시성, 플로우 경험, 지식의 자기효능감, 개인성과기대가 사용의도에 영향을 미치는 변수임을 밝혀내었다.

• The Journal of Information Systems
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• v.21 no.1
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• pp.69-91
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• 2012

The study investigates the media distinctiveness between twitter and other social media and describes how product information interpretation and responsiveness by internet users can be affected by the distinctive characteristics of twitter and blog media. The characteristics include relationship formation patterns among users, channel diversity, immediateness of information communication, information flow within media, media credibility, and management cost. Specifically, we statistically tested whether these characteristics are meaningfully differentiated by users. Results also showed that users perceived product information processing level and product evaluation direction differently based on these media characteristics. The current findings can serve as a pioneering work to provide a theoretical framework for examining social media characteristics and their impacts on consumer perception. In addition, this study practically suggests that marketers and network managers need to use differentiated communication strategies for twitters as a marketing strategic option.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.339-344
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• 2010

오늘날 인터넷 사용자들은 블로그나 뉴스 등의 매체에서 트랙백을 사용해 자신의 의견을 보다 자유롭게 나타낸다. 그러나 이러한 자유로움을 악용해 트랙백 스팸을 유발하여 네트워크의 자원을 낭비하고 방문자들에게 잘못된 정보를 전달해 해당 포스트의 신뢰를 떨어뜨린다. 트랙백 스팸은 유명한 포스트와 연계하여 자신의 포스트로 사용자들을 유도하는 특징을 가지기 때문에 일반적인 웹 스팸을 탐지하는 기술을 적용하기 어렵다. 따라서 본 논문에서는 자신이 작성한 글이 다른 사람의 글과 관련이 있다고 생각하여 다른사람의 글에 자신의 글을 링크시키는 트랙백의 특성을 이용하여 원본 페이지와 트랙백 페이지 그리고 트랙백 페이지의 아웃링크 내용상의 유사도와 동시 출현(co-occurrence) 정보를 이용하여 트랙백 스팸을 처리하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.905-906
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• 2009

오늘날 사회의 많은 조직들은 치열한 경쟁에서 살아남기 위해 고비용을 투자하여 고유한 경험, 연구 노하우, 신기술과 같은 새로운 지식을 축적하고 이를 잘 관리하기 위하여 지식관리시스템을 구축한다. 하지만, 시스템이 잘 구축됐음에도 불구하고 사용자의 낮은 활용으로 인하여 실패하는 사례가 발생한다. 본 논문에서는 이러한 점을 극복하기 위하여 기간 시스템과의 연계를 통한 지식 획득 방안을 제시하고 본 연구원에서 생산되는 자료의 특성인 공간정보를 관리할 수 있는 지식관리시스템을 소개하고자 한다.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.4
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• pp.33-49
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• 2019

The purpose of this study was to investigate the changes in the experiences of visitors of Yeonnam-dong during the period covering the development of a linear park, the Gyeongui Line Park. This study used a text mining technique to analyze Naver Blog postings of those who visited Yeonnam-dong from June 2013 to May 2017, divided into four periods -from June 2013 to May 2014, from June 2014 to May 2015, from June 2015 to May 2016 and from June 2016 to May 2017. The keywords used were 'Yeonnam-dong', 'Gyeongui Line' and 'Yeontral Park' and the data was further refined and resampled. A semantic network analysis was conducted on the basis of the co-occurrences of words. The results of the study were as follows. During the entire period, the main experience of visitors to Yeonnam-dong was 'food culture' consistently, but the activities related to 'market', 'browsing', and 'buy' increased. Also, activities such as 'walk', 'play' and 'rest' in the park newly appeared after the construction of the park. Moreover, more diverse opinions about the Yeonnam-dong were expressed on the blog, and Yeonnam-dong began to be recognized as a place where a variety of activities can be enjoyed. Lastly, when the visitors wrote about the theme 'food culture', the scope of the keywords expanded from simple ones, such as 'eat', 'photograph' and 'chatting' to 'market', 'browsing', and 'walk'. The sub-themes that appeared with the park also expanded to various topics with the emergence of the Gyeongui Line Book Street. This study analyzed the change of experiences of visitors objectively with text mining, a quantitative methodology. Due to the nature of text mining, however, the subjective opinions inevitably have been involved in the process of refining. Also, further research is required to assess the direct relationship between these changes and park construction.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.1-10
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• 2021

This study aimed to evaluate preferences of Bukhansan dulegil using sentiment analysis, a natural language processing technique, to derive preferred and non-preferred factors. Therefore, we collected blog articles written in 2019 and produced sentimental scores by the derivation of positive and negative words in the texts for 21 dulegil courses. Then, content analysis was conducted to determine which factors led visitors to prefer or dislike each course. In blogs written about Bukhansan dulegil, positive words appeared in approximately 73% of the content, and the percentage of positive documents was significantly higher than that of negative documents for each course. Through this, it can be seen that visitors generally had positive sentiments toward Bukhansan dulegil. Nevertheless, according to the sentiment score analysis, all 21 dulegil courses belonged to both the preferred and non-preferred courses. Among courses, visitors preferred less difficult courses, in which they could walk without a burden, and in which various landscape elements (visual, auditory, olfactory, etc.) were harmonious yet distinct. Furthermore, they preferred courses with various landscapes and landscape sequences. Additionally, visitors appreciated the presence of viewpoints, such as observation decks, as a significant factor and preferred courses with excellent accessibility and information provisions, such as information boards. Conversely, the dissatisfaction with the dulegil courses was due to noise caused by adjacent roads, excessive urban areas, and the inequality or difficulty of the course which was primarily attributed to insufficient information on the landscape or section of the course. The results of this study can serve not only serve as a guide in national parks but also in the management of nearby forest green areas to formulate a plan to repair and improve dulegil. Further, the sentiment analysis used in this study is meaningful in that it can continuously monitor actual users' responses towards natural areas. However, since it was evaluated based on a predefined sentiment dictionary, continuous updates are needed. Additionally, since there is a tendency to share positive content rather than negative views due to the nature of social media, it is necessary to compare and review the results of analysis, such as with on-site surveys.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.171-172
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• 2011

본 논문에서는 사람들의 관심사를 충족시킬 주제로, 소셜 네트워크(SNS)를 활성화 하여 다자간의 대화를 통한 비즈니스 마케팅을 유도하며 기존의 블로그 형식의 커뮤니티와 쇼핑몰의 형태를 결합한 신개념 네트워크를 제안하고 구현한다. 소셜 네트워크를 활성화 시키고, 패션이라는 주제로 사람들의 개성을 살릴 수 있는 아이템을 선정. 각자의 특성이 담긴 "아바타"를 제작, 본 논문 내에서 각자가 특성이 담긴 패셔니스타가 될 수 있는 공간이 된다. 실제 의류, 소품과 제법 유사하게 만든 이미지를 나와의 신체 비율이 비슷한 아바타에 직접 피팅을 시킬 수 있으며 자신이 직접 입어보지 않고, 시간과 공간의 제약을 받지 않는 것이 특징이다. 다자간의 실시간 커뮤니케이션을 통해 네트워킹도 활성화 될 뿐더러 기업과의 연계를 통해 구매로까지 이어질 수 있는 공간을 만든다.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.37-52
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• 2022

The purpose of this study is to analyze the demand for cultural ecosystem services in urban forests based on user perception and experience value by using Naver blog posts and LDA topic modeling. Bukhansan National Park was used to analyze and review the feasibility of spatial assessments. Based on the results of topic modeling from blog posts, a review process was conducted considering the relevance of Bukhansan National Park's cultural services and its suitability as a spatial assessment case, and finally, an index for the spatial assessment of urban forest's cultural service was derived. Specifically, 21 topics derived through topic analysis were interpreted, and 13 topics related to cultural ecosystem services were derived based on the MA(Millennium Ecosystem Assessment)'s classification system for ecosystem services. 72.7% of all documents reviewed had data deemed useful for this study. The contents of the topic fell into one of the seven types of cultural services related to "mountainous recreation activities" (23.7%), "indirect use value linked to tourism and convenience facilities" (12.4%), "inspirational activities" (11.2%), "seasonal recreation activities" (6.2%), "natural appreciation and static recreation activities" (3.7%). Next, for the 13 cultural service topics derived from data gathered about Bukhansan National Park, the possibility of spatial assessment of the characteristics of cultural ecosystem services provided by urban forests was reviewed, and a total of 8 cultural service indicators were derived. The MA's cultural service classification system for ecosystem services, which was widely used in previous studies, has limitations in that it does not reflect the actual user demand of urban forests, but it is meaningful in that it categorizes cultural service indicators suitable for domestic circumstances. In addition, the study is significant as it presented a methodology to interpret and derive the demand for cultural services using a large amount of user awareness and experience data.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.3
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• pp.89-102
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• 2024

This study aims to examine the characteristics of the user experience of New Town neighborhood parks and explore issues that diversify the experience of the parks. In order to quantitatively analyze a large amount of park visitors' experiences, text-based Naver blog reviews were collected and analyzed. Among the Phase 1 and 2 New Towns, the parks with the highest user experience postings were selected for each city as the target of analysis. Blog text data was collected from May 20, 2003, to May 31, 2022, and analysis was conducted targeting Ilsan Lake Park, Bundang Yuldong Park, Gwanggyo Lake Park, and Dongtan Lake Park. The findings revealed that all four parks were used for everyday relaxation and recreation. Second, the analysis underscores park's diverse user groups. Third, the programs for parks nearby were also related to park usage. Fourth, the words within the top 20 rankings represented distinctive park elements or content/programs specific to each park. Lastly, the results of the network analysis delineated four overarching types of park users and the networks of four park user types appeared differently depending on the park. This study provides two implications. First, in addition to the naturalistic characteristics, the differentiation of each park's unique facilities and programs greatly improves public awareness and enriches the individual park experience. Second, if analysis of the context surrounding the park based on spatial information is performed in addition to text analysis, the accuracy of interpretation of text data analysis results could be improved. The results of this study can be used in the planning and designing of parks and greenspaces in the Phase 3 New Towns currently in progress.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.163-176
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• 2014

Social media is becoming the platform for users to communicate their activities, status, emotions, and experiences to other people. In recent years, microblogs, such as Twitter, have gained in popularity because of its ease of use, speed, and reach. Compared to a conventional web blog, a microblog lowers users' efforts and investment for content generation by recommending shorter posts. There has been a lot research into capturing the social phenomena and analyzing the chatter of microblogs. However, measuring television ratings has been given little attention so far. Currently, the most common method to measure TV ratings uses an electronic metering device installed in a small number of sampled households. Microblogs allow users to post short messages, share daily updates, and conveniently keep in touch. In a similar way, microblog users are interacting with each other while watching television or movies, or visiting a new place. In order to measure TV ratings, some features are significant during certain hours of the day, or days of the week, whereas these same features are meaningless during other time periods. Thus, the importance of features can change during the day, and a model capturing the time sensitive relevance is required to estimate TV ratings. Therefore, modeling time-related characteristics of features should be a key when measuring the TV ratings through microblogs. We show that capturing time-dependency of features in measuring TV ratings is vitally necessary for improving their accuracy. To explore the relationship between the content of microblogs and TV ratings, we collected Twitter data using the Get Search component of the Twitter REST API from January 2013 to October 2013. There are about 300 thousand posts in our data set for the experiment. After excluding data such as adverting or promoted tweets, we selected 149 thousand tweets for analysis. The number of tweets reaches its maximum level on the broadcasting day and increases rapidly around the broadcasting time. This result is stems from the characteristics of the public channel, which broadcasts the program at the predetermined time. From our analysis, we find that count-based features such as the number of tweets or retweets have a low correlation with TV ratings. This result implies that a simple tweet rate does not reflect the satisfaction or response to the TV programs. Content-based features extracted from the content of tweets have a relatively high correlation with TV ratings. Further, some emoticons or newly coined words that are not tagged in the morpheme extraction process have a strong relationship with TV ratings. We find that there is a time-dependency in the correlation of features between the before and after broadcasting time. Since the TV program is broadcast at the predetermined time regularly, users post tweets expressing their expectation for the program or disappointment over not being able to watch the program. The highly correlated features before the broadcast are different from the features after broadcasting. This result explains that the relevance of words with TV programs can change according to the time of the tweets. Among the 336 words that fulfill the minimum requirements for candidate features, 145 words have the highest correlation before the broadcasting time, whereas 68 words reach the highest correlation after broadcasting. Interestingly, some words that express the impossibility of watching the program show a high relevance, despite containing a negative meaning. Understanding the time-dependency of features can be helpful in improving the accuracy of TV ratings measurement. This research contributes a basis to estimate the response to or satisfaction with the broadcasted programs using the time dependency of words in Twitter chatter. More research is needed to refine the methodology for predicting or measuring TV ratings.