• Title/Summary/Keyword: 네이버포스트

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A Study of E-Book Production Lessons Using SNS Type on the Academic Achievement and Learning Attitudes of Elementary School Students (SNS형식의 전자책 제작 수업을 통한 초등학생의 학업 성취도 및 학습 태도 연구)

  • Kim, Daehui;Park, Phanwoo
    • Journal of The Korean Association of Information Education
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    • v.20 no.1
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    • pp.29-38
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    • 2016
  • This study selected and utilized the 'Naver post' as an e-book production tool to be used for learning. The production of such SNS format e-books aimed at founding out its effect on learning attitude and academic achievement by stimulating interest and confidence in the learning of the students. To accomplish such an aim, the study selected 50 students from two classes in the fourth grade of a public elementary school. One class of 25 students went through a social studies lesson that applied SNS type e-book production activities, and the other class of 25 students underwent a regular social studies lesson as the comparative group. The major results of the study's analysis is SNS type e-book production did not significantly improve academic achievement in social studies, but SNS type e-book production significantly improved the learning attitude during social studies.

A Study on Detecting Fake Reviews Using Machine Learning: Focusing on User Behavior Analysis (머신러닝을 활용한 가짜리뷰 탐지 연구: 사용자 행동 분석을 중심으로)

  • Lee, Min Cheol;Yoon, Hyun Shik
    • Knowledge Management Research
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    • v.21 no.3
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    • pp.177-195
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    • 2020
  • The social consciousness on fake reviews has triggered researchers to suggest ways to cope with them by analyzing contents of fake reviews or finding ways to discover them by means of structural characteristics of them. This research tried to collect data from blog posts in Naver and detect habitual patterns users use unconsciously by variables extracted from blogs and blog posts by a machine learning model and wanted to use the technique in predicting fake reviews. Data analysis showed that there was a very high relationship between the number of all the posts registered in the blog of the writer of the related writing and the date when it was registered. And, it was found that, as model to detect advertising reviews, Random Forest is the most suitable. If a review is predicted to be an advertising one by the model suggested in this research, it is very likely that it is fake review, and that it violates the guidelines on investigation into markings and advertising regarding recommendation and guarantee in the Law of Marking and Advertising. The fact that, instead of using analysis of morphemes in contents of writings, this research adopts behavior analysis of the writer, and, based on such an approach, collects characteristic data of blogs and blog posts not by manual works, but by automated system, and discerns whether a certain writing is advertising or not is expected to have positive effects on improving efficiency and effectiveness in detecting fake reviews.

Research on public sentiment of the post-corona new normal: Through social media (SNS) big data analysis (포스트 코로나 뉴노멀에 대한 대중감성 연구: 소셜미디어(SNS) 빅데이터 분석을 통해)

  • Ann, Myung-suk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.2
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    • pp.209-215
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    • 2022
  • In this study, detailed factors of public sentiment toward the 'post-corona new normal' were examined through social media big data sentiment analysis. Thus, it is to provide basic data to preemptively cope with the post-COVID-19 era. For data collection and analysis, the emotional analysis program of 'Textom', a big data analysis program, was used. The data collection period is one year from October 5, 2020 to October 5, 2021, and the collection channels are set as blogs, cafes, Twitter, and Facebook on Daum and Naver. The original data edited and refined a total of 3,770 collected texts from this channel were used for this study. The conclusion is as follows. First, there is a high level of interest and liking for the 'post-corona new normal'. In other words, it can be seen that optimism such as daily recovery, technological growth, and expectations for a new future took the lead at 77.62%. Second, negative emotions such as sadness and rejection are 22.38% of the total, but the intensity of emotions is 23.91%, which is higher than the ratio, suggesting that these negative emotions are intense. This study has a contribution to the detailed factor analysis of the public's positive and negative emotions through big data analysis on the 'post-corona new normal'.

A Study on the Operation Plans for Seongnam Public Library Programs in the Post-COVID-19 Era (포스트 코로나 시대 성남시 도서관의 문화프로그램 운영 방안 연구)

  • Song, Min Sun
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.177-186
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    • 2022
  • The purpose of this study is to suggest operation plans for library programs in preparation for the post-COVID-19 by analyzing the current status of library programs before and after the outbreak of COVID-19 based on the data of the Seongnam public libraries on the Public Data Portal. So, based on 1,317 data collected through the data purification process for duplicates and errors in the files uploaded by Seongnam City, ①programs' subject & type, ②program target users, ③program operation types(online or offline), ④program operating time & number of days, ⑤characteristics of programs preferred by users etc. were analyzed. As results of the analysis, online programs were not operated at all before COVID-19, but online programs started to be operated in earnest after August 2020. Also, there were many experiential activity lectures for infants and elementary school students in 2019, but reading activity lectures for adults and elementary school students increased in 2020. There were many types of online lectures, such as real-time lectures using online video conferencing programs, YouTube video viewing & live broadcasting, and the use of Naver Band & Cafe.

A Study on the Demand for Cultural Ecosystem Services in Urban Forests Using Topic Modeling (토픽모델링을 활용한 도시림의 문화서비스 수요 특성 분석)

  • Kim, Jee-Young;Son, Yong-Hoon
    • 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.

The Direction of Innovation in Curriculum of Universities in the Fourth Industrial Revolution

  • Hwang, Eui-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.11
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    • pp.229-238
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    • 2020
  • Upcoming 4th industrial revolution era and the post-covid19 made procedure, contents, and the ways of education innovative changes. Thesis analyzed the changes of educational procedures of universities unsing Bigkinds of 'KPF', (which is Korea Press Foundation) and DataLab system of 'Naver'. The following three results were derived from relational analysis, monthly keyword trend, and related word analysis with 633 cases searched for the keyword of "university curriculum innovation, creativity, and convergence." Firstly, the frequency of relationship keyword analysis of recent 4 years(2016~2020) was ministry of education(190), industrial revolution(154), system(137), career(136), global(131), smart(97), and enrolled students(95) in order. Secondly, The frequency of keywords related to the related words was Human Resources Development (136), Industrial-Academic Cooperation (119), Education Ministry (86), Specialization (69), and LiNC (62), which showed the importance of supporting the government (Ministry of Education) and fostering human resources, industry-academic cooperation, LiNC, and characterization in order to foster human resources in universities. According to this study, the paradigm of education is the artificial intelligence environment of the fourth industrial revolution, which is meaningful in presenting the direction of specialization, industry-academic cooperation, smart, and globalization, and the future direction of education that fosters creative talent in the era of the fourth industrial revolution.

Professional Baseball Viewing Culture Survey According to Corona 19 using Social Network Big Data (소셜네트워크 빅데이터를 활용한 코로나 19에 따른 프로야구 관람문화조사)

  • Kim, Gi-Tak
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.6
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    • pp.139-150
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    • 2020
  • The data processing of this study focuses on the textom and social media words about three areas: 'Corona 19 and professional baseball', 'Corona 19 and professional baseball', and 'Corona 19 and professional sports' The data was collected and refined in a web environment and then processed in batch, and the Ucinet6 program was used to visualize it. Specifically, the web environment was collected using Naver, Daum, and Google's channels, and was summarized into 30 words through expert meetings among the extracted words and used in the final study. 30 extracted words were visualized through a matrix, and a CONCOR analysis was performed to identify clusters of similarity and commonality of words. As a result of analysis, the clusters related to Corona 19 and Pro Baseball were composed of one central cluster and five peripheral clusters, and it was found that the contents related to the opening of professional baseball according to the corona 19 wave were mainly searched. The cluster related to Corona 19 and unrelated to professional baseball consisted of one central cluster and five peripheral clusters, and it was found that the keyword of the position of professional baseball related to the professional baseball game according to Corona 19 was mainly searched. Corona 19 and the cluster related to professional sports consisted of one central cluster and five peripheral clusters, and it was found that the keywords related to the start of professional sports according to the aftermath of Corona 19 were mainly searched.