• Title/Summary/Keyword: 소셜 데이터 분석

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A Study on Analysis of Flickr Note and Its Applications for Social Media Search (소셜 미디어 검색을 위한 Flickr Note의 분석 및 응용에 관한 연구)

  • Jeong, Jin-Woo;Hong, Hyun-Ki;Lee, Dong-Ho
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06a
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    • pp.49-52
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    • 2011
  • 본 연구에서는 Flickr에서 제공하는 어노테이션 기법 중 Note 서비스에 대한 다양한 분석 결과를 제공하고, 이를 기반으로 소셜 미디어 검색을 위한 Flickr Note의 응용 방안을 제안한다. Flickr Note는 기존의 태그 기반 검색에서 활용되는 태그와는 달리 이미지의 특정 영역 위에 직접적으로 할당되는 텍스트들의 집합이다. Flickr Note는 보다 지능적인 소셜 이미지 공유 및 검색 서비스를 위하여 다양한 정보들을 제공할 수 있는 중요한 데이터지만, 이를, 이미지 검색에 효과적으로 활용하기 위한 연구는 미미한 수준이다. 따라서 본 연구에서는 Flickr Note에 대한 다양한 분석을 통하여 소설 이미지 검색에서 Note의 역할 및 활용 기능성을 제공하고자 하며, 이를 바탕으로 Flickr Note 기반의 이미지 분석 및 검색을 위한 다양한 연구들이 시도되기를 기대한다.

An Epidemic Model for Sentiment Diffusion (소셜미디어상에서의 감성 전파 모델링 연구)

  • Woo, Jiyoung;Choi, Minn Seok;Lee, Min Jung
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2015.07a
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    • pp.81-83
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    • 2015
  • 본 연구는 사용자의 감성이 온라인 소셜 미디어를 통해 감염이 된다는 사실을 감성 전파 모델링으로 보이고자 한다. 이를 위해 전염병 파생을 기술하고 이를 예측하는데 사용되었던 질병확산 모델을 기초로 소셜 미디어상의 감성 전파 모델을 제시한다. 제시한 모델의 타당성을 검증하기 위해 특정 리테일 산업에 대한 논의가 활발히 이루어지고 있는 웹포럼의 데이터를 수집한다. 수집된 데이터로부터 주요 주제어를 도출하고, 주제별 감성을 측정하고, 시간에 따른 감성 값을 도출하여, 제시한 모델을 추정한다. 실험 결과 사용자의 긍정적 감성과 부정적 감성이 서로 경쟁관계에 있다는 가정을 따른 제안한 모델이 타당함을 보였다.

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Exploratory Approach of Social Gameplay Behavior Pattern : Case Study of World of Warcrafts (소셜 게임플레이 행동패턴의 탐색적 접근 : World of Warcrafts를 중심으로)

  • Song, Seung-Keun
    • The Journal of the Korea Contents Association
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    • v.13 no.5
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    • pp.37-47
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    • 2013
  • The objective of this research is to discover the rule of gameplay related to the task interdependence to analyse the behavior pattern of social gameplay. Previous literatures related to the gameplay were reviewed and game which was suitable for the gameplay of the task interdependence was selected. A party-play includes a team of five people in the experiment during the gameplay with think-aloud method and video/audio data about action protocol and verbal report were collected. The video observation and protocol analysis were conducted to analyse data. The objective coding scheme were developed from consolidated sequence model task analysis. The player's behavior was analysed. The result was revealed that four rules and four modified rules were included into the total eight behavior pattern. A behavior graph integrated with five gameplay was written. The excellent cooperative spot and error and failure place could be identified. The social gameplay behavior graph is expected to be the key practical design guideline on whether the level design and balance design are proper.

A Study on the Using of Social Network Services of Libraries in Korea (국내 도서관의 소셜네트워크서비스 실태조사)

  • Byeon, Hoi-Kyun;Cho, Hyun-Yang
    • Journal of Korean Library and Information Science Society
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    • v.44 no.4
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    • pp.255-275
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    • 2013
  • This study aims to examine the case of using the social network services in the korea library, and then search the type of social network services and the status of it's introduction. It is used to the study of the introduction and the invigoration of social network services on the compatible library. First, we extracted the list of four type's high level management libraries from 2010 to 2012. Second, we examined the website's homepage of the list of 32's university library, 41's public library, 40's school library, 9's special library. Third, the result of analysis identified the feature and difference of the using the social network services of these libraries. Fourth, on the base of the result, it suggested some items of introduction's issue and the directions of future research.

Different Look, Different Feel: Social Robot Design Evaluation Model Based on ABOT Attributes and Consumer Emotions (각인각색, 각봇각색: ABOT 속성과 소비자 감성 기반 소셜로봇 디자인평가 모형 개발)

  • Ha, Sangjip;Lee, Junsik;Yoo, In-Jin;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.55-78
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    • 2021
  • Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

A Study on Bi-LSTM-Based Drug Side Effects Post Detection Model in Social Network Service Data (소셜 네트워크 서비스 데이터에서 Bi-LSTM 기반 약물 부작용 게시물 탐지 모델 연구)

  • Lee, Chung-Chun;Lee, Seunghee;Song, Mi-Hwa;Lee, Suehyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.397-400
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    • 2022
  • 본 연구에서는 소셜 네트워크 서비스(Social Network Service, SNS) 데이터로부터 약물 부작용 게시글을 추출하기 위한 순환 신경망(Recurrent Neural Network, RNN) 기반 분류 모델을 제안한다. 먼저, 처방 빈도가 높으며 게시글을 많이 확보할 수 있는 케토프로펜 약물에 대하여 국내 최대 소셜 네트워크 플랫폼인 네이버 블로그와 카페의 게시글(2005 년~2020 년)을 확보하고 최종 3,828 건을 분석하였다. 결과적으로 케토프로펜에 대한 3 종(약물, 부작용, 불용어)의 렉시콘을 정의하였으며 이를 기반으로 Bi-LSTM 분류모델 기준 87%의 정확도를 얻었다. 본 연구에서 제안하는 모델은 SNS 데이터가 약물 부작용 정보 획득을 위한 기존 (전자의무기록, 자발적 약물 부작용 보고 시스템 등) 자료원에 대한 보완적 정보원이 되며, 개발된 Bi-LSTM 분류모델을 통해 약물 부작용 게시글 추출의 편리성을 제공할 것으로 기대된다.

Development of a Facebook Fan Pages Analysis System to Improve Public Relations Effect (홍보 효과 증진을 위한 페이스북 팬페이지 분석 시스템 개발)

  • Choi, Minseok
    • Journal of Digital Convergence
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    • v.13 no.12
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    • pp.135-142
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    • 2015
  • Appearance and rapid growth of the social network services (SNS) have led to changes in the distribution structure of information. Consumers can obtain various information quickly via the social network services and companies make use of a new advertising channel in them. In order to increase the effect of publicity activities through the social network services, development and application of public relations strategy by evaluating and analyzing the results of the activities is required. In this paper, a method for developing a low cost system to evaluate and analyze the results of public relations through the social networks is proposed. The proposed method was verified through building and running a demo system to collect and analyze data in the Facebook fan pages using MySQL database and PHP script on a Linux server.

An Analysis of the Relationship between Public Opinion on Social Bigdata and Results after Implementation of Public Policies: A Case Study in 'Welfare' Policy (소셜 빅데이터 기반 공공정책 국민의견 수렴과 정책 시행 이후 결과 관계 분석: '복지' 정책 사례를 중심으로)

  • Kim, Tae-Young;Kim, Yong;Oh, Hyo-Jung
    • Journal of Digital Convergence
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    • v.15 no.3
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    • pp.17-25
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    • 2017
  • Horizon scanning that one of the methods for future prediction is adaptable way of establishing the policy strategy based on big data. This study aims to understand the social problems scientifically utilized horizon scanning technique, and contribute to public policy formulation based on scanning analysis. In this paper, we proposed a public opinion framework for public policy based on social bigdata, and then confirmed the feasibility this framework by analysis of the relationship between public opinion and results after implementation of public policy. Consequently, based on the analysis, we also drew implications of policy formulation about 'free childcare for under 5-years of age' as an object of study. The method that collects public opinion is very important to effective policy establishment and make contribution to constructing national response systems for social development.

An Analysis of Relationship Between Word Frequency in Social Network Service Data and Crime Occurences (소셜 네트워크 서비스의 단어 빈도와 범죄 발생과의 관계 분석)

  • Kim, Yong-Woo;Kang, Hang-Bong
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.9
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    • pp.229-236
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    • 2016
  • In the past, crime prediction methods utilized previous records to accurately predict crime occurrences. Yet these crime prediction models had difficulty in updating immense data. To enhance the crime prediction methods, some approaches used social network service (SNS) data in crime prediction studies, but the relationship between SNS data and crime records has not been studied thoroughly. Hence, in this paper, we analyze the relationship between SNS data and criminal occurrences in the perspective of crime prediction. Using Latent Dirichlet Allocation (LDA), we extract tweets that included any words regarding criminal occurrences and analyze the changes in tweet frequency according to the crime records. We then calculate the number of tweets including crime related words and investigate accordingly depending on crime occurrences. Our experimental results demonstrate that there is a difference in crime related tweet occurrences when criminal activity occurs. Moreover, our results show that SNS data analysis will be helpful in crime prediction model as there are certain patterns in tweet occurrences before and after the crime.

COVID-19 and Korean Family Life on Social Media: A Topic Model Approach (소셜 빅데이터로 알아본 코로나19와 가족생활: 토픽모델 접근)

  • Park, Sunyoung;Lee, Jaerim
    • The Journal of the Korea Contents Association
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    • v.21 no.3
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    • pp.282-300
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    • 2021
  • The purpose of this study was to explore what social media posts tell us about family life during the COVID-19 pandemic by examining the keywords and topics underlying posts on blogs and online forums. Our criteria for web crawling were (a) blog and forum posts on Naver and Daum, the top portal sites in Korea, (b) posts between February 23 and April 19, 2020, the period of the first heightened social distancing orders, and (c) inclusion of "COVID" and "family" or "COVID" and "home." We analyzed 351,734 posts using TF-IDF values and topic modeling based on latent Dirichlet allocation. We identified and named 22 topics including COVID-19 prevention, family infection, family health, dietary life and changes, religious life, stuck at home, postponed school year, family events, travel and vacations, concerns about family and friends, anxiety and stress, disaster and damage, COVID-19 warning text messages, family support policies, Shin-cheon-ji and Daegu. The results show that COVID-19 impacted various domains of family life including health, food, housing, religion, child care, education, rituals, and leisure as well as relationships and emotions.