• Title/Summary/Keyword: 버즈량

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Analysis of Opinion Social Data on the SNS (Social Network Service) by Analyzing of Collective Damage Reply (악성 집단 댓글 분석에 의한 SNS 여론 소셜데이터 분석)

  • Hwang, Yun Chan;Koh, Chan
    • Journal of Digital Convergence
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    • v.11 no.5
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    • pp.41-51
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    • 2013
  • A lots of social data are distributed, utilized and opened through the social media. They have characterized effectiveness and pleasure of information to the media by social data but it is ignored about excessive exposure of information and damage from collective reply of personal attack type. In this paper, we study about analysis of opinion social data on the SNS (Social Network Service) by analyzing of collective damage reply. It is analysed by diverse measurement method for distribution and disuse of the amount of Buzz data that is analysed data from structured social network.

A Study on factors affecting the viewer rating of"My Little Television": Focusing on SNS Big Data (마이리틀 텔레비전 시청률에 영향을 미치는 요인에 관한 연구 : SNS 빅데이터 중심으로)

  • Kim, Sang-Cheol;Kim, Kwang-Ho
    • Journal of Digital Contents Society
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    • v.17 no.1
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    • pp.1-10
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    • 2016
  • < My Little Television > with the new format which extends one person media broadcasting to terrestrial broadcasting is creating a huge Topic Index. It started the first broadcast on April 2015 and has continued the number one in viewer rating in the same time. While viewers directly participate in the program through the Daum TV Pod and a host communicates with viewers in a real time, various opinions are being reflected on the program. While a lot of information about the program has spread through SNS, it has led to raising the viewer rating of program. Recently, the Topic Index on the program has been published through the big data analysis rather than the program evaluation only by the viewer rating. The research on the correlation between the program viewer rating and amount of buzz has increased. In this study, it has analyzed how the Topic Index which is an extended concept of the amount of buzz affects the viewer rating. Study results show that the Topic Index is analyzed to positively influence the viewer rating. It will give a lot of help in studying big data of SNS on the program.

Analysis of Trends in Icheon Airport using IIAC Trend Analysis Platform (인천공항 트렌드 분석 플랫폼을 이용한 2018년 인천공항 트렌드 분석)

  • Son, Seokhyun;Choi, Yu-Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.2-4
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    • 2019
  • 인천공항은 2001년 개항이후, 비약적으로 발전하고 있으며, 2018년 약 6500만 명의 여객을 수용하는 등 초대형 메가허브공항으로 도약 중이다. 2018년 인천공항은 제2여객터미널을 개장하며, 인천공항에 대한 언론과 대중의 관심을 증폭시켰고, 평창동계올림픽 개최와 남북정상회담을 통해 대한민국 중추공항으로서의 이미지를 각인시켰다. 인천국제공항공사는 인천공항의 건설 및 관리, 운영, 주변지역개발, 부대사업 및 기타 국가위탁사업을 하는 국토교통부 산하 공공기관으로 2018년 입국장 면세점 도입, 정규직 전환 등의 이슈를 생성하였다. 본 논문에서는 뉴스, SNS 수집, 저장, 처리, 분석플랫폼인 ITAP를 이용하여 인천공항, 인천국제공항공사 관련된 뉴스, SNS 내용을 플랫폼별로 분석하였고, 월별 버즈량과 주요키워드를 플랫폼별로 추출하여 2018년 인천공항, 인천국제공항공사의 주요 이슈를 제시한다.

Correlation analysis is needed to predict consumption and consumption prediction model using LSTM (상관관계 분석을 통한 소비예측 시 필요 요소 도출 및 LSTM을 이용한 소비예측 모델)

  • Lee, Kihoon;Kim, Jinah;Moon, Nammee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.05a
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    • pp.539-541
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    • 2019
  • 오프라인 소비자의 의사결정은 크게 라이프스타일, 동기, 개성, 학습 등 개인적인 영향요인과 문화, 기후, 가족 등 기타 상황적 요인을 포함하는 환경적 영향요인에 의해 결정된다. 이러한 요인들을 입력 값으로 하는 다양한 딥러닝 모델을 이용한 소비예측 연구들이 진행되고 있다. 딥러닝을 이용한 예측모델을 사용하기 위해서는 먼저 요인들이 의사를 결정하는데 있어 얼마나 상관관계가 있는지 파악하는 작업이 중요하다. 본 논문에서는 이를 위해 다양한 상관관계 분석모델을 이용해 소비 의사결정 요소 중 기후, 문화와 같은 상황적 요인과 소비와의 상관관계를 도출하고, 기후, 문화를 대변하는 미세먼지 데이터와, SNS 버즈량 데이터와 소비데이터를 학습하는 소비예측 LSTM모델을 제안하고자 한다.

Performance of Broadcasting Contents by Platforms (방송 플랫폼별 콘텐츠 유통 성과)

  • Kim, Suk;Song, Gin
    • The Journal of the Korea Contents Association
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    • v.15 no.12
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    • pp.81-96
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    • 2015
  • This study investigated the attributes of the popular programs by various broadcasting related platforms(on-air, VOD, SNS) and the relationship between the outcomes of these platforms in order to get the implications of broadcasting contents distribution strategy in multi-platform era. First, the study found that drama programs of territorial broadcasting showed the most high performance in on-air platform while comedy entertainment programs got the outstanding achievement in VOD platform. Second, although it had the low ratings in on-air platform, the program could be highly probable to get a great deal of VOD hits if it had attracted the younger audience. Knowledge programs showed the similar outcome between on-air and VOD platforms. Third, the study found that the factor which had a significant influence on VOD performance was the amount of buzz in SNS. These results suggest that broadcasting content distribution strategy in multi-platform era needs the understanding of the segmented target audiences of content and the analysis of trait of each platform.

A domain-specific sentiment lexicon construction method for stock index directionality (주가지수 방향성 예측을 위한 도메인 맞춤형 감성사전 구축방안)

  • Kim, Jae-Bong;Kim, Hyoung-Joong
    • Journal of Digital Contents Society
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    • v.18 no.3
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    • pp.585-592
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    • 2017
  • As development of personal devices have made everyday use of internet much easier than before, it is getting generalized to find information and share it through the social media. In particular, communities specialized in each field have become so powerful that they can significantly influence our society. Finally, businesses and governments pay attentions to reflecting their opinions in their strategies. The stock market fluctuates with various factors of society. In order to consider social trends, many studies have tried making use of bigdata analysis on stock market researches as well as traditional approaches using buzz amount. In the example at the top, the studies using text data such as newspaper articles are being published. In this paper, we analyzed the post of 'Paxnet', a securities specialists' site, to supplement the limitation of the news. Based on this, we help researchers analyze the sentiment of investors by generating a domain-specific sentiment lexicon for the stock market.

A Big-Data Analysis on Older Adult's Health and Safety Issues (노인의 건강 및 안전문제에 대한 빅데이터 분석)

  • Wang, Lin;Lee, Ju-Gyung;Hwang, Ji-Hyeon
    • The Journal of the Korea Contents Association
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    • v.19 no.4
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    • pp.336-344
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    • 2019
  • Currently, Korea is entering an aging society, causing the issues of older adults in a wide range of fields. This study focuses on the health and safety issues of the older adults. As a theoretical background, Maslow's hierarchy of needs theory was applied, and a new theory was established in connection with the physiological needs and safety needs of the 5 stages of desire in relation to the health and safety issues of the older adults. Health issues applying to physiological needs for the older adults are examined in detail in the body, perception and psychology areas, and safety accidents occurring indoors and outdoors are examined in relation to safety needs. Naver DataLab, a big data portal, shows that the number of bugs regarding health and safety of the older adults is steadily increasing. And through Google Trends, we can understand the interest setting up related search keyword about the older adults. According to the related search keywords, social part related to health in health issues is ranked high and kewords related to accident type in safety issues is ranked high. These findings will be an important basis data for research and solution to the issues of older adults.

Case Study of Big Data-Based Agri-food Recommendation System According to Types of Customers (빅데이터 기반 소비자 유형별 농식품 추천시스템 구축 사례)

  • Moon, Junghoon;Jang, Ikhoon;Choe, Young Chan;Kim, Jin Gyo;Bock, Gene
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.5
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    • pp.903-913
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    • 2015
  • The Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries launched a public data portal service in January 2015. The service provides customized information for consumers through an agri-food recommendation system built-in portal service. The recommendation system has fallowing characteristics. First, the system can increase recommendation accuracy by using a wide variety of agri-food related data, including SNS opinion mining, consumer's purchase data, climate data, and wholesale price data. Second, the system uses segmentation method based on consumer's lifestyle and megatrends factors to overcome the cold start problem. Third, the system recommends agri-foods to users reflecting various preference contextual factors by using recommendation algorithm, dirichlet-multinomial distribution. In addition, the system provides diverse information related to recommended agri-foods to increase interest in agri-food of service users.