• Title/Summary/Keyword: social data analysis

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Study of Mental Disorder Schizophrenia, based on Big Data

  • Hye-Sun Lee
    • International Journal of Advanced Culture Technology
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    • v.11 no.4
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    • pp.279-285
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    • 2023
  • This study provides academic implications by considering trends of domestic research regarding therapy for Mental disorder schizophrenia and psychosocial. For the analysis of this study, text mining with the use of R program and social network analysis method have been used and 65 papers have been collected The result of this study is as follows. First, collected data were visualized through analysis of keywords by using word cloud method. Second, keywords such as intervention, schizophrenia, research, patients, program, effect, society, mind, ability, function were recorded with highest frequency resulted from keyword frequency analysis. Third, LDA (latent Dirichlet allocation) topic modeling result showed that classified into 3 keywords: patient, subjects, intervention of psychosocial, efficacy of interventions. Fourth, the social network analysis results derived connectivity, closeness centrality, betweennes centrality. In conclusion, this study presents significant results as it provided basic rehabilitation data for schizophrenia and psychosocial therapy through new research methods by analyzing with big data method by proposing the results through visualization from seeking research trends of schizophrenia and psychosocial therapy through text mining and social network analysis.

Analysis of Outdoor Wear Consumer Characteristics and Leading Outdoor Wear Brands Using SNS Social Big Data (SNS 소셜 빅데이터를 통한 아웃도어 의류 소비자 특성과 주요 아웃도어 의류 브랜드 현황 분석)

  • Jung, Hye Jung;Oh, Kyung Wha
    • Fashion & Textile Research Journal
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    • v.18 no.1
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    • pp.48-62
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    • 2016
  • Consumers have come to demand high quality, affordable prices, and innovative product designs of the outdoor wear market due to their well-being and leisure oriented lifestyle. A new system of business in outdoor wear has emerged in the process through which corporations have endeavored to satisfy such consumer needs. Outdoor wear brands have utilized social network services (SNS) such as Facebook and Twitter as means of marketing and have built close relations with consumers based on communication through these media. Recently, explosively escalating SNS data are referred to as social big data, and now that every consumer online is a commentator, reviewer, and publisher, the outdoor wear market and all of its brands have to stop talking and start listening to how they are perceived. Therefore, this study employs Social $Metrics^{TM}$, a social big data analysis solution by Daumsoft, Inc., to verify changes in the allusions related to outdoor wear market found on SNS. This study aims to identify changes in consumer perceptions of outdoor wear based on changes in outdoor wear search words and trends in positive and negative public opinion found in SNS social big data. In addition, products of interest, the major brands mentioned, the attributes taken into consideration during purchases of products, and consumers' psychology were categorized and analyzed by means of keywords related to outdoor wear brands found on SNS. The results of this study will provide fundamental resources for outdoor wear brands' market entry and brand strategy implementation in the future.

Social Worker's Physical・Social Distance for People Living with HIV/AIDS (사회복지 업무 종사자의 HIV/AIDS 감염인에 대한 신체적・사회적 거리감)

  • Rhee, Young Sun;Lee, In Jeong
    • Korean Journal of Health Education and Promotion
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    • v.30 no.5
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    • pp.177-188
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    • 2013
  • Objectives: The purpose of this study was to evaluate the feeling of distance of social work practitioners for people living with HIV/AIDS(PLWHA) and to identify related factors. Methods: A total of 409 data were collected as convenience sampling from social welfare service providers. Independent variables were socio-demographic data, AIDS related knowledge, authoritarian personality, prejudice for minority(handicapped, women, foreigner, old aged), cultural competency. Data were analyzed by t-test, ANOVA, multiple regression analysis were conducted. Results: Multiple regression model was developed by integrating the significant variables from univariate analysis. Significant factors of physical distance were social prejudice against handicapped, knowledge about AIDS and critical awareness/knowledge about other culture. And significant factors of social distance were social prejudice against handicapped, knowledge about AIDS, authoritarian personality, critical awareness/knowledge about other culture. At last, we found that social prejudice against handicapped was the biggest factor for physical distance and authoritarian personality was the biggest factor for social distance of social work practitioners. Conclusions: The area of social services for PLWHA have to be expanded. Physical and social distance of professionals to provide services to PLWHA and factors affecting it is necessary to continue research. In addition, on the basis of these findings, specific training programs is need to be developed.

A Study on the Meaning of The First Slam Dunk Based on Text Mining and Semantic Network Analysis

  • Kyung-Won Byun
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.164-172
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    • 2023
  • In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

Comparative Analysis of the Status of Restaurant Start-ups Before and After the Lifting of Social Distancing Through Big Data Analysis

  • Jong-Hyun Park;Yang-Ja Bae;Jun-Ho Park;Gi-Hwan Ryu
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.353-360
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    • 2023
  • This paper explores notable shifts in the restaurant startup market following the lifting of social distancing measures. Key trends identified include an escalated interest in startups, a heightened focus on the quality and diversity of food, a relative decline in the importance of delivery services, and a growing interest in specific industry sectors. The study's data collection spanned three years, from April 2021 to May 2023, encompassing the period before and after social distancing. Data were sourced from a range of online platforms, including blogs, news sites, cafes, web documents, and intellectual forums, provided by Naver, Daum, and Google. From this collected data, the top 50 words were identified through a refinement process. The analysis was structured around the social distancing application period, comparing data from April 2021 to April 2022 with data from May 2022 to May 2023. These observed trend changes provide founders with valuable insights to seize new market opportunities and formulate effective startup strategies. In summary, We offer crucial insights for founders, enabling them to comprehend the evolving dynamics in food service startups and to adapt their strategies to the current market environment.

Nexus Between Social Media and Brand Preference of Smart Mobile Phones: An Empirical Study in Sri Lanka

  • KUMARADEEPAN, Vasanthakumar
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.8
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    • pp.241-249
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    • 2021
  • The aim of the research is to evaluate the impact of social media marketing (with special reference to Facebook) on the brand preference of customers with regard to smart mobile phones. Since Facebook has become very popular today and a trend has arisen to use social media as a marketing tool, the researcher intended to evaluate the impact of social media marketing on brand preference, as the findings would provide valuable insight for future businesses. Social media as measured social media visibility, social media engagement, and social media influencewas the independent variableand brand preference was the dependent variable. The convenience sampling method was used where the sample was taken from a group of people easy to contact or to reach. A sample of 186 young males and females was selected. Factor loading and factor analysis were used to analyze the data and find the most influencing factors on brand preference. Reliability analysis, validity analysis, and regression analysiswere performed to analyze the data. The R2 value is 0.320 implying that 32.00% of the variance in brand preference is explained by social media influence, social media engagement, and social media visibility. The findings show thatsocial media visibility, social media engagement, and social media influencehave a positive impact on brand preference.

A Study on Social Perception of Young Children with Disabilities through Social Media Big Data Analysis (소셜 미디어 빅데이터 분석을 통한 장애 유아에 대한 사회적 인식 연구)

  • Kim, Kyoung-Min
    • Journal of the Korea Convergence Society
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    • v.13 no.2
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    • pp.1-12
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    • 2022
  • The purpose of this study is to identify the social perception characteristics of young children with disabilities over the past decade. For this purpose, Textom, an Internet-based big data analysis system was used to collect data related to young children with disabilities posted on social media. 50 keywords were selected in the order of high frequency through the data cleaning process. For semantic network analysis, centrality analysis and CONCOR analysis were performed with UCINET6, and the analyzed data were visualized using NetDraw. As a result, the keywords such as 'education, needs, parents, and inclusion' ranked high in frequency, degree, and eigenvector centrality. In addition, the keywords of 'parent, teacher, problem, program, and counseling' ranked high in betweenness centrality. In CONCOR analysis, four clusters were formed centered on the keywords of 'disabilities, young child, diagnosis, and programs'. Based on these research results, the topics on social perception of young children with disabilities were investigated, and implications for each topic were discussed.

The Exploratory Study for the Application of the Sports Field in the Fourth Industrial Revolution: Focus on the Social Big Data (4차 산업혁명의 스포츠 현장 적용을 위한 탐색적 연구: 소셜 빅데이터 활용 방안을 중심으로)

  • Park, SungGeon;Hwang, YoungChan
    • 한국체육학회지인문사회과학편
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    • v.56 no.4
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    • pp.397-413
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    • 2017
  • The purpose of this study is to introduce the case and to provide related information for the physical education major to handle and utilize the social big data through the exploratory study for the application of sports industry in the fourth industrial revolution. For this study, data was collected from the article database, which covers the keyword such as 'Social Big Data', 'Sports' and so on. The analyzed articles were 86 articles. As a results, The research on social big data applied to sports industry are as follows: 1) Analysis of major issues related to sports fans' interests and sports events, 2) A study on media sports engagement, 3) The prediction analysis of sports game based on the sentiment analysis, 4) Development of salary estimation model for professional player in sports, 5) Research trend analysis and so on. In conclusion, the social big data analysis technology in the sports industry and management can be utilized variously. Therefore, the specialists of the sports industry and management field need to learn the techniques, to acquire the know-how for the research project, to convert the convergence thinking.

A exploratory study about a influenced position of social network formed by success factors cognition of Social Enterprises with importance : two-mode data (사회적 기업 성공요인 공유 관계와 사회네트워크 영향력 위치 탐색연구 : 투 모드 데이터를 중심으로)

  • Kim, Byung Suk;Choi, Jae Woong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.2
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    • pp.157-171
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    • 2014
  • A organization of social enterprises is to achieve various goals such as private interests, the public nature, and social policy. For fulfilling these goals, we have to understand the various success factors. These success factors were shared among peoples. This study explored a position of structure of social network formed by success factors of Social Enterprises with importance. A position within social network defined a number of link connected other nodes. A position is closely associated with to individual's behaviors, opinions and thinking. We used social network analysis with two mode method for explaining feathers of structure of social network formed by success factors shared among peoples. We choose degree centrality for determining a position within social network. Centrality is a key measure in social network analysis. Results is that shared success factors are operation capital(15.15%) totally, and by Buying experience of products of Social Enterprises, Business Compliance(14.39%) and planning(12.88%), and by usage time of smart devices, Business Support(17.05%) and planning(16.10%). and the dominant success factor was not explored.

Management Efficiency Estimation of Social Enterprises with Data Envelopment Analysis (사회적 기업의 자료포락분석(DEA)을 통한 경영효율성 평가)

  • Lee, Sang-Yun;Lim, Sungmook;Chae, Myungsin
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.2
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    • pp.121-128
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    • 2017
  • This paper was to evaluate social enterprises' management efficiency with Data Envelope Analysis (DEA). The data was based on the 168 social enterprises' of annual performance reports published in 2015. The research focused on to measure both financial efficiency and social impact of the companies simultaneously. To apply DEA, the paper classified the enterprises into seven types based on types of socal impacts which each company provides before the estimation of the efficiency. The research results showed that group D, which employes disadvantaged people, provides social services and shares resources was the most efficient group and had higest net worths in Pure Technical Efficiency. In contrast, Group B, which only employs social advantage people and provides social service, was the least efficient one. The research suggests a practical and efficient framework in measuring social enterprises' management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. Because the Korea Social Enterprise Promotion Agency does not open business reports which social enterprises submit each year, there are basic limitations on researchers attempting to analyse with data from all social enterprises in Korea. Thus, this study dealt with only 10% of the social enterprises which self-published their performance report on the Korea Social Enterprise Promotion Agency's web site. Regardless of these limitations, this study suggested substantial methods to estimate management efficiency with the self-published reports. Because self-publishing is increasing each year, it will be the main source of information for researchers in examining and evaluating social enterprises' financial performance or social contribution. The research suggests a practical and efficient framework in measuring social enterprises' management efficiency, including both the financial performance and social impacts simultaneously with their self-publishing reports. The research results suggest not only list of efficient enterprises but also methods of improvement for less efficient enterprises.