• Title/Summary/Keyword: Naver Trends

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Patent citation network analysis (특허 인용 네트워크 분석)

  • Lee, Minjung;Kim, Yongdai;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.613-625
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    • 2016
  • The development of technology has changed the world drastically. Patent data analysis helps to understand modern technology trends and predict prospective future technology. In this paper, we analyze the patent citation network using the USPTO data between 1985 and 2012 to identify technology trends. We use network centrality measures that include a PageRank algorithm to find core technologies and identify groups of technology with similar properties with statistical network models.

A Study on Major Uninsured Korean Medicine Treatments Search Trends and Their Meanings in an Online Portal: Using Naver Data Lab (온라인 포털에서의 주요 비급여 한의치료 검색 트렌드와 그 의미에 대한 고찰: 네이버 데이터랩을 이용하여)

  • Chan-Young Kwon
    • The Journal of Korean Medicine
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    • v.44 no.3
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    • pp.74-86
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    • 2023
  • Objectives: The purpose of this study was to examine search trends and their meanings for major uninsuired Korean medicine (KM) treatments through analysis of an online portal search results. Methods: Keywords searches were performed using Naver Datalab on 4 July 2023. From January 2016 to June 2023, monthly relative search volume (RSV) for keywords 'pharmacopuncture', 'Chuna', and 'needle-embedding therapy', and 'herbal decoction' were extracted with a score between 0 and 100. For the obtained RSVs, longitudinal changes over time, characteristics according to sex and age group, and correlations between them were investigated. Results: The ranking of RSV for each keyword has changed from 'Chuna', 'herbal decoction', 'needle-embedding therapy', and 'pharmacopuncture' to 'Chuna', 'herbal decoction', 'pharmacopuncture', and 'needle-embedding therapy' after 2019. Overall, the RSV of needle-embedding therapy continuously decreased, while that of pharmacopuncture continuously increased. In 2019, a rapid increase in the RSV of Chuna was observed, and in 2020, a rapid increase in the RSV of herbal decoction was observed. There was a difference in the longitudinal change pattern of RSV for the keywords by age group. Importantly, in the elderly, changes in RSV were observed in a favorable pattern to KM treatment. Conclusion: Our findings enable estimation of the public's interest and its changes for the four uninsuired KM treatment, and can be used as basic data to strengthen health insurance coverage in Korea. Specifically, changes in interest in KM treatments according to sex and age can be referred to.

Trends and Changes of Web Searching Behavior (웹 검색 행태의 추이 및 변화 분석)

  • Park, So-Yeon
    • Journal of the Korean Society for Library and Information Science
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    • v.45 no.1
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    • pp.377-393
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    • 2011
  • This study aims to investigate trends of internet searching behavior of users of NAVER, a major Korean search portal. In particular, this study analyzed trends of query submission behaviors, behaviors related to typos, multimedia searching behaviors, and click behaviors. In conducting this study, query logs and click logs of unified search service were analyzed. The results of this study show that there were little changes in the topic and length of queries, the pattern of typos, and multimedia seeking behavior over a year's period. However, click counts of documents have gradually increased over time. The results of this study can be implemented to increase the portal's effective development of internet contents and searching algorithms.

A Study on the Characteristics of Amekaji Fashion Trends Using Big Data Text Mining Analysis (빅데이터 텍스트 마이닝 분석을 활용한 아메카지 패션 트렌드 특징 고찰)

  • Kim, Gihyung
    • Journal of Fashion Business
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    • v.26 no.3
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    • pp.138-154
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    • 2022
  • The purpose of this study is to identify the characteristics of domestic American casual fashion trends using big data text mining analysis. 108,524 posts and 2,038,999 extracted keywords from Naver and Daum related to American casual fashion in the past 5 years were collected and refined by the Textom program, and frequency analysis, word cloud, N-gram, centrality analysis, and CONCOR analysis were performed. The frequency analysis, 'vintage', 'style', 'daily look', 'coordination', 'workwear', 'men's wear' appeared as the main keywords. The main nationality of the representative brands was Japanese, followed by American, Korean, and others. As a result of the CONCOR analysis, four clusters were derived: "general American casual trend", "vintage taste", "direct sales mania", and "American styling". This study results showed that Japanese American casual clothes are influenced by American casual clothes, and American casual fashion in Korea, which has been reinterpreted, is completed with various coordination and creative styles such as workwear, street, military, classic, etc., focusing on items and brands. Looks were worn and shared on social networks, and the existence of an active consumer group and market potential to obtain genuine products, ranging from second-hand transactions for limited edition vintages to individual transactions were also confirmed. The significance of this study is that it presented the characteristics of American casual fashion trends academically based on online text data that the public actually uses because it has been spread by the public.

A Study on the Trend Change of Restaurant Entrepreneurship through Big Data Analysis

  • Jong-Hyun Park;Yang-Ja Bae;Jun-Ho Park;Gi-Hwan Ryu
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.332-341
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    • 2023
  • Notable trends in the restaurant start-up market after the lifting of social distancing include increasing interest in start-ups, emphasizing the importance of food quality and diversity, decreasing the relative importance of delivery services, and increasing interest in certain industries. The data collection period is three years from April 2021 to May 2023, including before and after social distancing, and texts extracted from blogs, news, cafes, web documents, and intellectuals provided by Naver, Daum, and Google were collected. For the collected data, the top 30 words were derived through a refining process. In addition, based on April 2021, the application period of social distancing, data from April 2021 to April 2022, and data from May 2022 to May 2023, Through these changes in trends, founders can capture new opportunities in the market and develop start-up strategies. In conclusion, this paper provides important insights for founders in accurately understanding the changes in food service start-up trends and in developing strategies appropriate to the current market situation.

Analysis of Domestic Security Solution Market Trend using Big Data (빅데이터를 활용한 국내 보안솔루션 시장 동향 분석)

  • Park, Sangcheon;Park, Dongsoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.5
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    • pp.492-501
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    • 2019
  • To use the system safely in cyberspace, you need to use a security solution that is appropriate for your situation. In order to strengthen cyber security, it is necessary to accurately understand the flow of security from past to present and to prepare for various future threats. In this study, information security words of security/hacking news of Naver News which is reliable by using text mining were collected and analyzed. First, we checked the number of security news articles for the past seven years and analyzed the trends. Second, after confirming the security/hacking word rankings, we identified major concerns each year. Third, we analyzed the word of each security solution to see which security group is interested. Fourth, after separating the title and the body of the security news, security related words were extracted and analyzed. The fifth confirms trends and trends by detailed security solutions. Lastly, annual revenue and security word frequencies were analyzed. Through this big data news analysis, we will conduct an overall awareness survey on security solutions and analyze many unstructured data to analyze current market trends and provide information that can predict the future.

Trends of Search Behavior of Korean Web Users (국내 웹 이용자의 검색 행태 추이 분석)

  • Park Soyeon;Lee Joon Ho
    • Journal of the Korean Society for Library and Information Science
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    • v.39 no.2
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    • pp.147-160
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    • 2005
  • This study examines trends of web query types and topics submitted to NAVER during one year period by analyzing query logs and click logs. There was a seasonal difference in the distribution of query types. Query type distribution was also different between weekdays and weekends, and between different days of the week. The log data show seasonal changes in terms of the topics of queries. Search topics seem to change between weekdays and weekends, and between different days of the week. However, there was little change in overall patterns of search behavior across one year. The implications for system designers and web content providers are discussed.

Comparison and Analysis of Dieting Practices Using Big Data from 2010 and 2015 (빅데이터를 통한 2010년과 2015년의 다이어트 실태 비교 및 분석)

  • Jung, Eun-Jin;Chang, Un-Jae
    • Korean Journal of Community Nutrition
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    • v.23 no.2
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    • pp.128-136
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    • 2018
  • Objectives: The purpose of this study was to compare and analyse dieting practices and tendencies in 2010 and 2015 using big data. Methods: Keywords related to diet were collected from the portal site Naver from January 1, 2010 until December 31, 2010 for 2010 data and from January 1, 2015 until December 31, 2015 for 2015 data. Collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis, and seasonality analysis. Results: The results show that exercise had the highest frequency in simple frequency analysis in both years. However, weight reduction in 2010 and diet menu in 2015 appeared most frequently in N-gram analysis. In addition, keyword network analysis was categorized into three groups in 2010 (diet group, exercise group, and commercial weight control group) and four groups in 2015 (diet group, exercise group, commercial program for weight control group, and commercial food for weight control group). Analysis of seasonality showed that subjects' interests in diets increased steadily from February to July, although subjects were most interested in diets in July in both years. Conclusions: In this study, the number of data in 2015 steadily increased compared with 2010, and diet grouping could be further subdivided. In addition, it can be confirmed that a similar pattern appeared over a one-year cycle in 2010 and 2015. Therefore, dietary method is reflected in society, and it changes according to trends.

An Analysis on Anti-Drone Technology Trends of Domestic Companies Using News Crawling on the Web (뉴스 기사의 크롤링을 통한 국내 기업의 안티 드론에 사용되는 기술 현황 분석)

  • Kim, Kyuseok
    • Journal of Advanced Navigation Technology
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    • v.24 no.6
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    • pp.458-464
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    • 2020
  • Drones are being spreaded for the purposes such as construction, logistics, scientific research, recording, toy and so on. However, anti-drone related technologies which make the opposite drones neutralized are also widely being researched and developed because some drones are being used for crime or terror. The range of anti-drone related technologies can be divided into detection, identification and neutralization. The drone neutralization methods are divided into Soft-kill one which blocks the detected drones using jamming and Hard-kill one which destroys the detected ones physically. In this paper, Google and Naver domestic news articles related to anti-drone were gathered. Analyzing the domestic news articles, 8 of related technologies using RF, GNSS, Radar and so on were found. Regarding as this, the general features and usage status of those technologies were described and those on anti-drone for each company and agency were gathered and analyzed.

A Study on Big Data Based Investment Strategy Using Internet Search Trends (인터넷 검색추세를 활용한 빅데이터 기반의 주식투자전략에 대한 연구)

  • Kim, Minsoo;Koo, Pyunghoi
    • Journal of the Korean Operations Research and Management Science Society
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    • v.38 no.4
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    • pp.53-63
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    • 2013
  • Together with soaring interest on Big Data, now there are vigorous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, however, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other areas like Korea can be a disturbing task. This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.