• Title/Summary/Keyword: Keyword Trends

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Analysis on the Trends of Studies Related to the National Competency Standard in Korea throughout the Semantic Network Analysis (언어네트워크 분석을 적용한 국가직무능력표준(NCS) 연구 동향 분석)

  • Lim, Yun-Jin;Son, Da-Mi
    • 대한공업교육학회지
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    • v.41 no.2
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    • pp.48-68
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    • 2016
  • This study was conducted to identify the NCS-related research trends, Keywords, the Keywords Networks and the extension of the Keywords using the sementic network analysis and to seek for the development plans about NCS. For this, the study searched 345 the papers, with the National Competency Standards or NCS as a key word, among master's theses, dissertations and scholarly journals that RISS provides, and selected a total of 345 papers. Annual frequency analysis of the selected papers was carried out, and Semantic Network Analysis was carried out for 68 key words which can be seen as key terms of the terms shown by the subject. The method of analysis were KrKwic software, UCINET6.0 and NetDraw. The study results were as follows: First, NCS-related research increased gradually after starting in 2002, and has been accomplishing a significant growth since 2014. Second, as a result of analysis of keyword network, 'NCS, development, curriculum, analysis, application, job, university, education,' etc. appeared as priority key words. Third, as a result of sub-cluster analysis of NCS-related research, it was classified into four clusters, which could be seen as a research related to a specific strategy for realization of NCS's purpose, an exploratory research on improvement in core competency and exploration of college students' possibility related to employment using NCS, an operational research for junior college-centered curriculum and reorganization of the specialized subject, and an analysis of demand and perception of a high school-level vocational education curriculum. Fourth, the connection forming process among key words of domestic study results about NCS was expanding in the form of 'job${\rightarrow}$job ability${\rightarrow}$NCS${\rightarrow}$education${\rightarrow}$process, curriculum${\rightarrow}$development, university${\rightarrow}$analysis, utilization${\rightarrow}$qualification, application, improvement${\rightarrow}$plan, operation, industry${\rightarrow}$design${\rightarrow}$evaluation.'

International Research Trends Related to Inquiry in Science Education: Perception and Perspective on Inquiry, Support and Strategy for Inquiry, and Teacher Professional Development for Inquiry (과학교육에서 탐구 관련 국외 연구 동향 -탐구의 인식과 관점, 전략과 지원, 교사 전문성의 관점에서-)

  • Yu, Eun-Jeong;Byun, Taejin;Baek, Jongho;Shim, Hyeon-Pyo;Ryu, Kumbok;Lee, Dongwon
    • Journal of The Korean Association For Science Education
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    • v.41 no.1
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    • pp.33-46
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    • 2021
  • Inquiry occupies an important place in science education, and research related to inquiry is widely conducted. However, due to the inclusiveness of the concept of "exploration," each researcher perceives its meaning differently, and approaches may vary. In addition, criticisms have been raised that the results of classes using inquiry in science education do not guarantee meaningful changes to students. Therefore, this study attempts to identify the trend of SSCI-level research papers dealing with inquiry in science education over the past three years to confirm the current status and effectiveness of the inquiry. Researches used in the analysis are International Journal of Science Education, Journal of Research in Science Teaching, Research in Science Education, and Science Education, and limited to those that directly suggest "inquiry (enquiry)" as a keyword. Based on extracted 75 papers, the classification process was conducted, and an analysis frame was derived inductively by reflecting the subject and characteristics. Specific cases for each category were presented by dividing into three aspects: perception and perspective on inquiry, support and strategy for inquiry, and teacher professional development for inquiry. The results of examining the implications for scientific inquiry are as follows: First, rather than defining inquiry as an implicit proposition or presenting it as a step-by-step procedure, it was induced to grasp the meaning of inquiry more comprehensively and holistically. Second, as to whether the inquiry-based instruction is effective in all aspects of the cognitive, functional, and affective domains of science, the limitations are clearly presented, and the context-dependent and subject-specific properties and limitations of inquiry are emphasized. Third, uncertainty in science inquiry-based instruction can help learners to begin their inquiry and develop interest, but in the process of recognizing data and restructuring knowledge, explicit and specific guidance and scaffolding should be provided at an appropriate timing.

Multi-Category Sentiment Analysis for Social Opinion Related to Artificial Intelligence on Social Media (소셜 미디어 상에서의 인공지능 관련 사회적 여론에 대한 다 범주 감성 분석)

  • Lee, Sang Won;Choi, Chang Wook;Kim, Dong Sung;Yeo, Woon Young;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.51-66
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    • 2018
  • As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

Comparative Analysis of the Keywords in Taekwondo News Articles by Year: Applying Topic Modeling Method (태권도 뉴스기사의 연도별 주제어 비교분석: 토픽모델링 적용)

  • Jeon, Minsoo;Lim, Hyosung
    • Journal of Digital Convergence
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    • v.19 no.11
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    • pp.575-583
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    • 2021
  • This study aims to analyze Taekwondo trends according to news articles by year by applying topic modeling. In order to examine the Taekwondo trend through media reports, articles including news articles and Taekwondo specialized media articles were collected through Big Kinds of the Korea Press Foundation. The search period was divided into three sections: before 2000, 2001~2010, and 2011~2020. A total of 12,124 items were selected as research data. For topic analysis, pre-processing was performed, and topic analysis was performed using the LDA algorithm. In this case, python 3 was applied for all analysis. First, as a result of analyzing the topics of media articles by year, 'World' was the most common keyword before 2000. 'South and North Korea' was next common and 'Olympic' was the third commonest topic. From 2001 to 2010, 'World' was the most common topic, followed by 'Association' and 'World Taekwondo'. From 2011 to 2020, 'World', 'Demonstration', and 'Kukkiwon' was the most common topic in that order. Second, as a result of analyzing news articles before 2000 by topic modeling, topics were divided into two categories. Specifically, Topic 1 was selected as 'South-North Korea sports exchange' and Topic 2 was selected as 'Adoption of Olympic demonstration events'. Third, as a result of analyzing news articles from 2001 to 2010 by topic modeling, three topics were selected. Topic 1 was selected as 'Taekwondo Demonstration Performance and Corruption', Topic 2 was selected as 'Muju Taekwondo Park Creation', and Topic 3 was selected as 'World Taekwondo Festival'. Fourth, as a result of analyzing news articles from 2011 to 2020 by topic modeling, three topics were selected. Topic 1 was selected as 'Successful Hosting of the 2018 Pyeongchang Winter Olympics', Topic 2 was selected as 'North-South Korea Taekwondo Joint Demonstration Performance', and Topic 3 was selected as '2017 Muju World Taekwondo Championships'.

Exploring the Trend of Korean Creative Dance by Analyzing Research Topics : Application of Text Mining (연구주제 분석을 통한 한국창작무용 경향 탐색 : 텍스트 마이닝의 적용)

  • Yoo, Ji-Young;Kim, Woo-Kyung
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.6
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    • pp.53-60
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    • 2020
  • The study is based on the assumption that the trend of phenomena and trends in research are contextually consistent. Therefore the purpose of this study is to explore the trend of dance through the subject analysis of the Korean creative dance study by utilizing text mining. Thus, 1,291 words were analyzed in the 616 journal title, which were established on the paper search website. The collection, refining and analysis of the data were all R 3.6.0 SW. According to the study, keywords representing the times were frequently used before the 2000s, but Korean creative dance research types were also found in terms of education and physical training. Second, the frequency of keywords related to the dance troupe's performance was high after the 2000s, but it was confirmed that Choi Seung-hee was still in an important position in the study of Korean creative dance. Third, an analysis of the overall research subjects of the Korean creative dance study showed that the research on 'Art of Choi Seung-hee in the modern era' was the highest proportion. Fourth, the Hot Topics, which are rising as of 2000, appeared as 'the performance activities of the National Dance Company' and 'the choreography expression and utilization of traditional dance'. However, since the recent trend of the National Dance Company's performance is advocating 'modernization based on tradition', it has been confirmed that the trend of Korean creative dance since the 2000s has been focused on the use of traditional dance motifs. Fifth, the Cold Topic, which has been falling as of 2000, has been shown to be a study of 'dancing expressions by age'. It was judged that interest in research also decreased due to the tendency to mix various dance styles after the establishment of the genre of Korean creative dance.

A Study on Industry-specific Sustainability Strategy: Analyzing ESG Reports and News Articles (산업별 지속가능경영 전략 고찰: ESG 보고서와 뉴스 기사를 중심으로)

  • WonHee Kim;YoungOk Kwon
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.287-316
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    • 2023
  • As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

Analysis of the Impact of Generative AI based on Crunchbase: Before and After the Emergence of ChatGPT (Crunchbase를 바탕으로 한 Generative AI 영향 분석: ChatGPT 등장 전·후를 중심으로)

  • Nayun Kim;Youngjung Geum
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.53-68
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    • 2024
  • Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

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Mediating Roles of Attachment for Information Sharing in Social Media: Social Capital Theory Perspective (소셜 미디어에서 정보공유를 위한 애착의 매개역할: 사회적 자본이론 관점)

  • Chung, Namho;Han, Hee Jeong;Koo, Chulmo
    • Asia pacific journal of information systems
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    • v.22 no.4
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    • pp.101-123
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    • 2012
  • Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

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Intelligent Brand Positioning Visualization System Based on Web Search Traffic Information : Focusing on Tablet PC (웹검색 트래픽 정보를 활용한 지능형 브랜드 포지셔닝 시스템 : 태블릿 PC 사례를 중심으로)

  • Jun, Seung-Pyo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.93-111
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    • 2013
  • As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.