• Title/Summary/Keyword: Semantic Social Network

Search Result 169, Processing Time 0.031 seconds

A Collaborative Framework for Discovering the Organizational Structure of Social Networks Using NER Based on NLP (NLP기반 NER을 이용해 소셜 네트워크의 조직 구조 탐색을 위한 협력 프레임 워크)

  • Elijorde, Frank I.;Yang, Hyun-Ho;Lee, Jae-Wan
    • Journal of Internet Computing and Services
    • /
    • v.13 no.2
    • /
    • pp.99-108
    • /
    • 2012
  • Many methods had been developed to improve the accuracy of extracting information from a vast amount of data. This paper combined a number of natural language processing methods such as NER (named entity recognition), sentence extraction, and part of speech tagging to carry out text analysis. The data source is comprised of texts obtained from the web using a domain-specific data extraction agent. A framework for the extraction of information from unstructured data was developed using the aforementioned natural language processing methods. We simulated the performance of our work in the extraction and analysis of texts for the detection of organizational structures. Simulation shows that our study outperformed other NER classifiers such as MUC and CoNLL on information extraction.

A Study on the Analysis of Museum Gamification Keywords Using Social Media Big Data

  • Jeon, Se-won;Choi, YounHee;Moon, Seok-Jae;Yoo, Kyung-Mi;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.13 no.4
    • /
    • pp.66-71
    • /
    • 2021
  • The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

A Study on Recognition of Robot Barista Using Social Media Text Mining (소셜미디어 텍스트마이닝을 활용한 로봇 바리스타 인식 탐색 연구)

  • Han Jangheon;An Kabsoo
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.20 no.2
    • /
    • pp.37-47
    • /
    • 2024
  • The food tech market, which uses artificial intelligence robots for the restaurant industry, is gradually expanding. Among them, the robot barista, a representative food tech case for the restaurant industry, is characterized by increasing the efficiency of operators and providing things for visitors to see and enjoy through a 24-hour unmanned operation. This research was conducted through text mining analysis to examine trends related to robot baristas in the restaurant industry. The research results are as follows. First, keywords such as coffee, cafe, certification, ordering, taste, interest, people, robot cafe, coffee barista expert, free, course, unmanned, and wine sommelier were highly frequent. Second, time, variety, possibility, people, process, operation, service, and thought showed high closeness centrality. Third, as a result of CONCOR analysis, a total of 5 keyword clusters with high relevance to the restaurant industry were formed. In order to activate robot barista in the future, it is necessary to pay more attention to functional development that can strengthen its functions and features, as well as online promotion through various events and SNS in the robot barista cafe.

A Study on User Perception of Tourism Platform Using Big Data

  • Se-won Jeon;Sung-Woo Park;Youn Ju Ahn;Gi-Hwan Ryu
    • International journal of advanced smart convergence
    • /
    • v.13 no.1
    • /
    • pp.108-113
    • /
    • 2024
  • The purpose of this study is to analyze user perceptions of tourism platforms through big data. Data were collected from Naver, Daum, and Google as big data analysis channels. Using semantic network analysis with the keyword 'tourism platform,' a total of 29,265 words were collected. The collection period was set for two years, from August 31, 2021, to August 31, 2023. Keywords were analyzed for connected networks using TexTom and Ucinet programs for social network analysis. Keywords perceived by tourism platform users include 'travel,' 'diverse,' 'online,' 'service,' 'tourists,' 'reservation,' 'provision,' and 'region.' CONCOR analysis revealed four groups: 'platform information,' 'tourism information and products,' 'activation strategies for tourism platforms,' and 'tourism destination market.' This study aims to expand and activate services that meet the needs and preferences of users in the tourism field, as well as platforms tailored to the changing market, based on user perception, current status, and trend data on tourism platforms.

An Analysis of News Report Characteristics on Archives & Records Management for the Press in Korea: Based on 1999~2018 News Big Data (뉴스 빅데이터를 이용한 우리나라 언론의 기록관리 분야 보도 특성 분석: 1999~2018 뉴스를 중심으로)

  • Han, Seunghee
    • Journal of the Korean Society for information Management
    • /
    • v.35 no.3
    • /
    • pp.41-75
    • /
    • 2018
  • The purpose of this study is to analyze the characteristics of Korean media on the topic of archives & records management based on time-series analysis. In this study, from January, 1999 to June, 2018, 4,680 news articles on archives & records management topics were extracted from BigKinds. In order to examine the characteristics of the media coverage on the archives & records management topic, this study was analyzed to the difference of the press coverage by period, subject, and type of the media. In addition, this study was conducted word-frequency based content analysis and semantic network analysis to investigate the content characteristics of media on the subject. Based on these results, this study was analyzed to the differences of media coverage by period, subject, and type of media. As a result, the news in the field of records management showed that there was a difference in the amount of news coverage and news contents by period, subject, and type of media. The amount of news coverage began to increase after the Presidential Records Management Act was enacted in 2007, and the largest amount of news was reported in 2013. Daily newspapers and financial newspapers reported the largest amount of news. As a result of analyzing news reports, during the first 10 years after 1999, news topics were formed around the issues arising from the application and diffusion process of the concept of archives & records management. However, since the enactment of the Presidential Records Management Act, archives & records management has become a major factor in political and social issues, and a large amount of political and social news has been reported.

Text Mining Analysis of Media Coverage of Maritime Sports: Perceptions of Yachting, Rowing, and Canoeing (텍스트마이닝을 활용한 해양스포츠에 대한 언론 보도기사 분석: 요트, 조정, 카누를 중심으로)

  • Ji-Hyeon Kim;Bo-Kyeong Kim
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.29 no.6
    • /
    • pp.609-619
    • /
    • 2023
  • This study aimed to investigate the formation of the social perception of domestic maritime sports using text mining analysis of keywords and topics from domestic media coverage over the past 10 years related to representative maritime sports, including yachting, rowing, and canoeing. The results are as follows: First, term frequency (TF) and word cloud analyses identified the top keywords: "maritime," "competition," "experience," "tourism," "world," "yachting," "canoeing," "leisure," and "participation." Second, semantic network analysis revealed that yachting was correlated with terms like "maritime," "industry," "competition," "leisure," "tourism," "boat," "facilities," and "business"; rowing with terms like "competition" and "Chungju"; and canoeing with terms like "maritime," "competition," "experience," "leisure," and "tourism." Third, topic modeling analysis indicated that yachting, rowing, and canoeing are perceived as elite sports and maritime leisure sports. However, the perception of these sports has been demonstrated to have little impact on society, public opinion, and social transformation. In summary, when considering these results comprehensively, it can be concluded that yachting and canoeing have gradually shifted from being perceived as elite sports to essential elements of the maritime leisure industry. Contrariwise, rowing remains primarily associated with elite sports, and its popularization as a maritime leisure sport appears limited at this time.

Networked Structure and Message Types of Newspaper Advertisements about Universities in Daegu and Gyeongbuk provinces in Korea: A Social Network Analysis (사회연결망 분석을 활용한 대학의 신문광고 게재 구조와 메시지 유형: 대구·경북 지역을 중심으로)

  • Song, Hwa-Young;Kim, Jae-Hun;Park, Han-Woo
    • The Journal of the Korea Contents Association
    • /
    • v.21 no.6
    • /
    • pp.197-206
    • /
    • 2021
  • This study examined the networked structure and message types of newspapers advertisements in which universities have put in Daegu and Gyeongbuk provinces in Korea. Data were collected from July to September in 2020. As a result, universities preferred newspapers located in Daegu and Pohang areas. Next, universities have emphasized their cooperations with industries, basic competency capacities, and specialization programs in the advertising messages. When analyzing the findings in terms of university level, key words related to mid- to long-term development plans often appeared in the four-year schools. On the other hand, two or three-year universities frequently used an appeal that emphasized tangible performances. The findings showed the way in which the direction of university newspaper advertisements have been set in line with the rapidly changing environment.

A Study on the Efficient Countermeasures of Military in Accordance with Changing Security Environments (4차 산업혁명에 따른 군사보안 발전방안 연구)

  • Kim, Doo Hwan;Park, Ho Jeong
    • Convergence Security Journal
    • /
    • v.20 no.4
    • /
    • pp.47-59
    • /
    • 2020
  • The Army, which is dreaming of a military leap forward through the fourth industrial revolution, needs to also consider the side effects and adverse functions of the fourth industrial revolution. In particular, this study conducted an analysis of whether it was consistent with the global technological trend of normal 'military security'. This paper focuses on the countermeasures that could result from 4th industrial revolution by utilizing the text-mining technique and social network technique of big data. 1. Active promotion of a convergence program with private, public, militaryand industrial, academic, and solidarity, 2. Information Sharing for International Cooperation and Cooperation in Cyber security, 3. Military Innovation and Military Unsymmetric Cyber security innovation, 4.The Establishment of Military Security Convergence Interface Management System in accordance with the Fourth Industrial Revolution, 5. Cooperation in the transition from technology engineering to social technology, 6. Establishing a military security governance system in the military, 7. Specifying confidential military digital data We look forward to providing useful information so that the results of this study can help develop the military and enhance military confidentiality.

Content Analysis of Presidents' Addresses of English Literary Societies in Korea: Focusing on Analysis of a Language Network (영어영문학 관련 학회장 인사말 내용분석 - 언어네트워크분석을 중심으로)

  • Choi, Kyoungho;Mun, Gil Seong
    • The Journal of the Korea Contents Association
    • /
    • v.13 no.3
    • /
    • pp.495-501
    • /
    • 2013
  • The words a speaker uses can be regarded as the core, the main issue and a symbolic icon of what he says. Applying this to presidents' addresses of each English literary society in Korea shows that frequency in use and the linkage of words they use in their addresses are value and ideas executive officers pursue. The purpose of this study is to analyze the contents of presidents' addresses introduced in home page of each English literary society in Korea and investigate features and constitution of them each, focusing on analysis of a language network. The results of this study show the features of resemblances and differences of commonly-used words. In addition, these results appear to suggest that they can be also applied to a comparative study between the English literary societies in Korea.

A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling (임신성 당뇨와 모유수유에 대한 연구 동향 분석: 텍스트네트워크 분석과 토픽모델링 중심)

  • Lee, Junglim;Kim, Youngji;Kwak, Eunju;Park, Seungmi
    • The Journal of Korean Academic Society of Nursing Education
    • /
    • v.27 no.2
    • /
    • pp.175-185
    • /
    • 2021
  • Purpose: The aim of this study was to identify core keywords and topic groups in the 'Gestational diabetes mellitus (GDM) and Breastfeeding' field of research for better understanding research trends in the past 20 years. Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups. Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', 'fetus', 'hypoglycemia', 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were 'cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: 'cardiovascular disease', 'obesity', 'complication prevention strategy', 'support of breastfeeding', 'educational program' and 'management of GDM'. Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.