• Title/Summary/Keyword: 소셜미디어 평가

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A Study on improvement of performance of collaborative filtering recommendation system using social data (소셜 데이터를 이용한 협업필터링 추천 시스템 성능 개선 연구)

  • Joo, Jong-Min;Yang, Hyung-Jeong;Kim, Nam-Hun;Park, Sung-Hyun;Lee, Gun-Woo
    • Annual Conference of KIPS
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    • 2017.11a
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    • pp.660-663
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    • 2017
  • 다양한 소셜 네트워크 서비스가 발달되고 많은 사람들이 소셜 미디어에 참여하면서 방대한 양의 정보가 발생하고 있다. 따라서 원하는 정보를 선별하고 가공하는 연구도 활발히 진행되고 있다. 협업필터링은 이러한 정보를 토대로 사용자에게 맞춤형 아이템을 추천해주는 알고리즘이다. 하지만 정확한 추천을 위해서는 매우 방대한 양의 정보가 필요하다. 또한 협업필터링에는 초기에는 제대로 추천이 이루어지지 않는 콜드스타터 문제가 있다. 이러한 문제를 해결하기 위해 본 논문에서는 소셜 네트워크 서비스 중의 하나인 트위터 데이터를 활용하여 협업필터링 추천 시스템의 성능을 높이고자 한다. 협업필터링의 평점에 특정 아이템 관련 트윗을 수집해서 긍정/부정을 측정하여 가중치를 부여한다. RMSE 평가 방법을 통한 실험 결과, 소셜 미디어의 긍부정 영향력을 측정하여 적용했을 때가 기존의 협업필터링 방식에 비해 약 5.5%의 성능 향상을 확인하였다.

Employee's Business Outlook Disclosed Through Social Media And Employment Growth : The Case of Jobplanet (소셜미디어를 통한 직원의 기업전망 평가와 고용증가와의 상관성 : 잡플래닛 기업전망을 대상으로)

  • Byeongsoo, Kim;Ju Young, Kang
    • Smart Media Journal
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    • v.11 no.10
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    • pp.9-21
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    • 2022
  • The recent expansion of the use of social media has served as an opportunity to express users' opinions in real time in various fields such as society, economy, politics, and culture, and brought many platforms that provide various information about companies. Among them, Glassdoor.com which started 2008 in US provides users with evaluations of the current and the former employees of their companies and also provides a outlooks for the company's growth Such a platform has the utility of providing necessary information to whom want to find a job or change jobs. In addition to this, variable studies have shown that the company information provided through these platforms is useful for investors as well. In this study, it was tested whether the corporate growth prospects of employees provided by Jobplanet, a platform with a typical function similar to Glassdoor.com in Korea, have predictive power to predict actual corporate growth. The forecast provided by Jobplanet and the company's financial indicator data received from FnGuide were collected and composed of panel data and analyzed using fixed effect model regression analysis. As a result, it was found that companies with positive prospects had higher employment growth than companies with negative prospects. When the outlook was neutral, the employment growth rate was higher than that of companies with a negative outlook.

The Study on the Activation of Public Library Services Utilizing Twitter (트위터를 활용한 공공도서관 서비스 활성화 방안 연구)

  • Oh, Eui-Kyung
    • Journal of Information Management
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    • v.43 no.2
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    • pp.133-150
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    • 2012
  • This study showed the activation of public library services utilizing twitter. Top five American public library twitter's 1,373 tweets collected, analyzed by content types and examined applicability into public library services. Based on the results, it suggested that public library services can be activated by auto-tweeting informations within home page, re-tweeting of timely informations, generating HASH tag, using diverse social medias, active re-tweeting/replying, and utilizing twitter programs such as twit-bot. Finally, the study proposed that evaluations about twitter services such as satisfaction survey should be carried out.

Building and Analyzing Panic Disorder Social Media Corpus for Automatic Deep Learning Classification Model (딥러닝 자동 분류 모델을 위한 공황장애 소셜미디어 코퍼스 구축 및 분석)

  • Lee, Soobin;Kim, Seongdeok;Lee, Juhee;Ko, Youngsoo;Song, Min
    • Journal of the Korean Society for information Management
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    • v.38 no.2
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    • pp.153-172
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    • 2021
  • This study is to create a deep learning based classification model to examine the characteristics of panic disorder and to classify the panic disorder tendency literature by the panic disorder corpus constructed for the present study. For this purpose, 5,884 documents of the panic disorder corpus collected from social media were directly annotated based on the mental disease diagnosis manual and were classified into panic disorder-prone and non-panic-disorder documents. Then, TF-IDF scores were calculated and word co-occurrence analysis was performed to analyze the lexical characteristics of the corpus. In addition, the co-occurrence between the symptom frequency measurement and the annotated symptom was calculated to analyze the characteristics of panic disorder symptoms and the relationship between symptoms. We also conducted the performance evaluation for a deep learning based classification model. Three pre-trained models, BERT multi-lingual, KoBERT, and KcBERT, were adopted for classification model, and KcBERT showed the best performance among them. This study demonstrated that it can help early diagnosis and treatment of people suffering from related symptoms by examining the characteristics of panic disorder and expand the field of mental illness research to social media.

A Web Contents Ranking Algorithm using Bookmarks and Tag Information on Social Bookmarking System (소셜 북마킹 시스템에서의 북마크와 태그 정보를 활용한 웹 콘텐츠 랭킹 알고리즘)

  • Park, Su-Jin;Lee, Si-Hwa;Hwang, Dae-Hoon
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1245-1255
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    • 2010
  • In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

Korea-U.S. Relationship appearing in the Newspaper and Social Media: Based on the news and information related to the (언론과 소셜미디어를 통해 살펴본 한미관계: <한미정상회담> 관련 뉴스와 정보를 중심으로)

  • Hong, Juhyun
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.459-468
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    • 2022
  • This study searched and analyzed news and information on the Korea-U.S. Summit to explore which political agenda is spreading among Korean newspapers and social media. The result of the analysis revealed that, on the one hand, the conservative-leaning newspaper, Chosunilbo, covered the unresolved issue between two countries. The principal source of news was the opposition party. On the other hand, the progressive-leaning newspaper, Kyunghany Sinmun, highlighted President Moon's visit to the United States and described the visit to the United States as an achievement. In this paper, the principal source of news is the ruling party. Both conservative and the progressive newspapers did not present a negative view of the United States. In the case of Chosunilbo, it mentioned that foreign policy priority of President Biden is human rights in North Korea. If the two countries do not solve this issue, the relationship between Korea and the United States will not develop further. Second, I searched YouTube videos about the Korea-U.S. summit and conducted a network analysis to understand the influence of YouTube videos and explore their relationship the each other. The results of the analysis revealed that the 10 most influential videos portrayed the Moon government positively. These videos held the achievement of the visit to the United States in highly esteem and framed it positively, similarly to the progressive newspaper.

A Study on the Estimation of Character Value in Media Works: Based on Network Centralities and Web-Search Data (미디어 작품 캐릭터 가치 측정 연구: 네트워크 중심성 척도와 검색 데이터를 활용하여)

  • Cho, Seonghyun;Lee, Minhyung;Choi, HanByeol Stella;Lee, Heeseok
    • Knowledge Management Research
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    • v.22 no.4
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    • pp.1-26
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    • 2021
  • Measuring the intangible asset has been vigorously studied for its importance. Especially, the value of character in media industry is difficult to quantitatively evaluate in spite of the industry's rapid growth. Recently, the Social Network Analysis (i.e., SNA) has been actively applied to understand human usage patterns in a media field. By using SNA methodology, this study attempts to investigate how the character network characteristics of media works are linked to human search behaviors. Our analysis reveals the positive correlation and causality between character network centralities and character search data. This result implies that the character network can be used as a clue for the valuation of character assets.

Capstone Design Coaching Model with SNS (SNS기반 캡스톤설계 코칭모델)

  • Oh, Soo Lyul
    • Smart Media Journal
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    • v.5 no.2
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    • pp.8-14
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    • 2016
  • In this paper, we propose a model for coaching and formal operating procedures performed capstone design advisor during the design done to allow effective guidance and management. Coaching model is proposed through coaching and capstone design proposed by coaching on the procedure for the implementation and management, Mokpo National University Department of Computer Engineering student in the program outcomes, performance assessment of the effective operation of the capstone design based social network service the demonstrated effectiveness of the coaching model.

Information Sharing Intention in a Social Media Platform: A Study of Participants in the Chinese WeChat Moments (소셜미디어 플랫폼에서의 정보공유 의도: 중국 위챗 이용자에 대한 연구)

  • Seok Noh;Li Zhao;Bong Jae Kang
    • Information Systems Review
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    • v.24 no.1
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    • pp.89-104
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    • 2022
  • This study proposes a model for evaluating social media platform members' information-sharing intention toward WeChat moments. The data comes from Chinese WeChat users, and 150 WeChat users participated in this survey. The results of this study reveal that information-sharing intention is influenced directly by attitude, subjective norms, and perceived behavioral control, whereas reputation and friendship-reciprocity are positively related attitude; the impression is positively related to perceived behavioral control on information sharing.

Identification of Visitation Density and Critical Management Area Regarding Marine Spatial Planning: Applying Social Big Data (해양공간계획 수립을 위한 방문밀집도 및 중점관리지역 규명: 소셜 빅데이터를 활용하여)

  • Kim, Yoonjung;Kim, Choongki;Kim, Gangsun
    • Journal of Environmental Impact Assessment
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    • v.29 no.2
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    • pp.122-131
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    • 2020
  • Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.