• Title, Summary, Keyword: 소셜네트워크 인식

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An Insight Study on Keyword of IoT Utilizing Big Data Analysis (빅데이터 분석을 활용한 사물인터넷 키워드에 관한 조망)

  • Nam, Soo-Tai;Kim, Do-Goan;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.146-147
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    • 2017
  • Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

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Automatic Tagging Scheme for Plural Faces (다중 얼굴 태깅 자동화)

  • Lee, Chung-Yeon;Lee, Jae-Dong;Chin, Seong-Ah
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.3
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    • pp.11-21
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    • 2010
  • To aim at improving performance and reflecting user's needs of retrieval, the number of researches has been actively conducted in recent year as the quantity of information and generation of the web pages exceedingly increase. One of alternative approaches can be a tagging system. It makes users be able to provide a representation of metadata including writings, pictures, and movies etc. called tag and be convenient in use of retrieval of internet resources. Tags similar to keywords play a critical role in maintaining target pages. However, they still needs time consuming labors to annotate tags, which sometimes are found to be a hinderance caused by overuse of tagging. In this paper, we present an automatic tagging scheme for a solution of current tagging system conveying drawbacks and inconveniences. To realize the approach, face recognition-based tagging system on SNS is proposed by building a face area detection procedure, linear-based classification and boosting algorithm. The proposed novel approach of tagging service can increase possibilities that utilized SNS more efficiently. Experimental results and performance analysis are shown as well.

Public Perception and Usage Pattern of Science Museum by Social Media Big Data Analysis (소셜 빅데이터 분석을 통해 알아본 대중의 과학관에 대한 인식 및 사용 행태)

  • Yun, Eunjeong;Park, Yunebae
    • Journal of The Korean Association For Science Education
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    • v.37 no.6
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    • pp.1005-1014
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    • 2017
  • Focusing on the role of the science museum as an institution to improve the scientific literacy of the public, this study investigated public perception and behavior about science museum to know how much science museums affect the public by using social media big data analysis. For this purpose, we extracted texts containing 'science museum' in Naver blogs and Twitter, analyzed them by using network, frequency, co-ocurrence, and semantics analysis and compared them with the results in English speaking countries. As a result, blogs were mainly concerned with science museum among parents who have young children, while in Twitter posts from many students who visited as a group appeared. Therefore, the Korean public used science museum mainly as a space for children's experience, and in this case, programs and exhibitions of science museums are perceived positively. On the other hand, students who visited as a group showed some negative emotions. The result of comparison with the cases of foreign countries in terms of the function of the third generation science museum such as communications with the science museum and the public and the participation of the public in science, the Korean public hardly mentioned the scientific contents, words related to communications such as 'argue', and curators or staff after visiting the science museum. In contrast to many verbs related to meaningful activities such as 'learn', 'participate', 'listen', 'read', 'ask', 'think' appeared in English, only a small number of verbs include 'ask' and 'thin' appeared in Korean. Therefore, science museum need to improve impression, communicating with public, and involving activity with impact and variety after visit.

Effects of Customers' Relationship Networks on Organizational Performance: Focusing on Facebook Fan Page (고객 간 관계 네트워크가 조직성과에 미치는 영향: 페이스북 기업 팬페이지를 중심으로)

  • Jeon, Su-Hyeon;Kwahk, Kee-Young
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.57-79
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    • 2016
  • It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

Impact social networking service characteristics and audience' relationship experiences on the degree of acceptance (소셜네트워크서비스 특성과 수용자 관계성경험이 수용의도에 미치는 영향)

  • Joung, Jin-Tak
    • Journal of Digital Convergence
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    • v.15 no.4
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    • pp.107-115
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    • 2017
  • This study examined the SNS Factors and user awareness evaluate the relationship affect the degree of acceptance SNS. Additionally, the effect on the SNS uses the social media attributes and user relationship was confirmed what the critical factors applied. Through literature analysis, SNS characteristic factors were selected to interactivity and exchange views and usability, and relationship factors were selected the flow and attachment orientation. And these factors and verified the effect on the SNS also acceptable. It was accomplished by a regression analysis to achieve the purpose of research. results were as follows. First, the interactivity and exchange of ideas and useful characteristics had a significant impact on the SNS acceptance. Second, SNS relationship characteristic of flow and attached propensity has had a significant impact on the SNS acceptance. Third, SNS relationship factors are more influential than the SNS features a great degree of acceptance. These results will provide suggestions for necessary to have any experience as well as SNS should emphasize what characteristics you want the communicator to accommodate the height of SNS also allows the use of SNS users.

The Result of Question Investigation about the Awareness of Light Pollution in Korea

  • Cho, Jaesang;Lee, Won-Chul;Lim, Hyung-Jin;Sul, Ah-Chim
    • The Bulletin of The Korean Astronomical Society
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    • v.39 no.1
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    • pp.89.1-89.1
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    • 2014
  • 빛공해란, 불필요하거나 필요 이상의 인공빛이 야생 동식물들과 우리 인간들에게 악영향을 미치는 현상을 말하며, 실생활에서 인공빛 에너지를 목적에 맞지 않게 사용하는 것이 이 현상의 주요 원인이라고 할 수 있다. 빛공해 현상은 야생 동식물들에게 악영향을 주어 개체수를 감소시킬뿐만 아니라 멸종에까지 이르게 할 수 있으며, 지구 자전의 영향으로 하루 24시간 주기로 설정되어 있는 우리 인간의 생체리듬을 교란시켜 암, 비만, 당뇨병, 그리고 우울증 등과 같은 인간의 목숨을 위협할 수 있는 질병들을 일으키기도 한다. 하지만 인공빛을 목적에 맞게 올바르게 사용한다면 그로 인해 절약된 에너지와 그 비용을 다른 필요한 분야에 대체하여 사용할 수 있을 것이다. 우리는 과거의 빛공해 관련 논문과 보고서의 설문조사 결과를 통하여 빛공해로 인한 피해와 에너지 낭비 문제가 빛공해에 대한 일반 시민들의 무관심으로부터 발생하고 있다는 사실을 확인할 수 있었다. 따라서 우리는 빛공해에 대한 일반 시민들의 인식 변화를 알아보기 위하여 기존에 진행된 설문조사와 같은 문답내용의 설문조사를 올해 다시 실시하였다. 그 설문조사의 결과를 통하여 우리는 과거보다 빛공해에 대한 인식이 많이 확산되어 있다는 사실을 알 수 있었으며, 그 이유로는 최근 빛공해와 관련된 많은 뉴스 기사들과 함께 웹상의 소셜네트워크와 같은 다양한 경로의 정보매체들을 통하여 빛공해에 대한 정보를 보다 빠르고 쉽게 접할 수 있는 환경이 조성되었기 때문이라고 분석하였다. 빛공해 인식 확산에 더욱 더 기여하기 위하여 최근에 우리는 국제 어두운 밤하늘 협회 한국 지부 (Korean Chapter, International Dark-Sky Association) 인가를 받아 그 단체 이름으로 빛공해 방지 홍보 사업을 온라인과 오프라인을 통하여 보다 더 활발히 진행하기 위하여 많은 노력을 하고 있다.

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Identifying Landscape Perceptions of Visitors' to the Taean Coast National Park Using Social Media Data - Focused on Kkotji Beach, Sinduri Coastal Sand Dune, and Manlipo Beach - (소셜미디어 데이터를 활용한 태안해안국립공원 방문객의 경관인식 파악 - 꽃지해수욕장·신두리해안사구·만리포해수욕장을 대상으로 -)

  • Lee, Sung-Hee;Son, Yong-Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.46 no.5
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    • pp.10-21
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    • 2018
  • This study used text mining methodology to focus on the perceptions of the landscape embedded in text that users spontaneously uploaded to the "Taean Travel"blogpost. The study area is the Taean Coast National Park. Most of the places that are searched by 'Taean Travel' on the blog were located in the Taean Coast National Park. We conducted a network analysis on the top three places and extracted keywords related to the landscape. Finally, using a centrality and cohesion analysis, we derived landscape perceptions and the major characteristics of those landscapes. As a result of the study, it was possible to identify the main tourist places in Taean, the individual landscape experience, and the landscape perception in specific places. There were three different types of landscape characteristics: atmosphere-related keywords, which appeared in Kkotji Beach, symbolic image-related keywords appeared in Sinduri Coastal Sand Dune, and landscape objects-related appeared in Manlipo Beach. It can be inferred that the characteristics of these three places are perceived differently. Kkotji Beach is recognized as a place to appreciate a view the sunset and is a base for the Taean Coast National Park's trekking course. Sinduri Coastal Sand Dune is recognized as a place with unusual scenery, and is an ecologically valuable space. Finally, Manlipo Beach is adjacent to the Chunlipo Arboretum, which is often visited by tourists, and the beach itself is recognized as a place with an impressive appearance. Social media data is very useful because it can enable analysis of various types of contents that are not from an expert's point of view. In this study, we used social media data to analyze various aspects of how people perceive and enjoy landscapes by integrating various content, such as landscape objects, images, and activities. However, because social media data may be amplified or distorted by users' memories and perceptions, field surveys are needed to verify the results of this study.

A Dynamic Management Method for FOAF Using RSS and OLAP cube (RSS와 OLAP 큐브를 이용한 FOAF의 동적 관리 기법)

  • Sohn, Jong-Soo;Chung, In-Jeong
    • Journal of Intelligence and Information Systems
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    • v.17 no.2
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    • pp.39-60
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    • 2011
  • Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

Design and Implementation of Personal Information Identification and Masking System Based on Image Recognition (이미지 인식 기반 향상된 개인정보 식별 및 마스킹 시스템 설계 및 구현)

  • Park, Seok-Cheon
    • The Journal of The Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.1-8
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    • 2017
  • Recently, with the development of ICT technology such as cloud and mobile, image utilization through social networks is increasing rapidly. These images contain personal information, and personal information leakage accidents may occur. As a result, studies are underway to recognize and mask personal information in images. However, optical character recognition, which recognizes personal information in images, varies greatly depending on brightness, contrast, and distortion, and Korean recognition is insufficient. Therefore, in this paper, we design and implement a personal information identification and masking system based on image recognition through deep learning application using CNN algorithm based on optical character recognition method. Also, the proposed system and optical character recognition compares and evaluates the recognition rate of personal information on the same image and measures the face recognition rate of the proposed system. Test results show that the recognition rate of personal information in the proposed system is 32.7% higher than that of optical character recognition and the face recognition rate is 86.6%.