• Title/Summary/Keyword: naver trend

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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.

Investment Strategies for KOSPI Index Using Big Data Trends of Financial Market (금융시장의 빅데이터 트렌드를 이용한 주가지수 투자 전략)

  • Shin, Hyun Joon;Ra, Hyunwoo
    • Korean Management Science Review
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    • v.32 no.3
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    • pp.91-103
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    • 2015
  • This study recognizes that there is a correlation between the movement of the financial market and the sentimental changes of the public participating directly or indirectly in the market, and applies the relationship to investment strategies for stock market. The concerns that market participants have about the economy can be transformed to the search terms that internet users query on search engines, and search volume of a specific term over time can be understood as the economic trend of big data. Under the hypothesis that the time when the economic concerns start increasing precedes the decline in the stock market price and vice versa, this study proposes three investment strategies using casuality between price of domestic stock market and search volume from Naver trends, and verifies the hypothesis. The computational results illustrate the potential that combining extensive behavioral data sets offers for a better understanding of collective human behavior in domestic stock market.

Induced Abortion Trends and Prevention Strategy Using Social Big-Data (소셜 빅데이터를 이용한 낙태의 경향성과 정책적 예방전략)

  • Park, Myung-Bae;Chae, Seong Hyun;Lim, Jinseop;Kim, Chun-Bae
    • Health Policy and Management
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    • v.27 no.3
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    • pp.241-246
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    • 2017
  • Background: The purpose of this study is to investigate the trends on the induced abortion in Korea using social big-data and confirm whether there was time series trends and seasonal characteristics in induced abortion. Methods: From October 1, 2007 to October 24, 2016, we used Naver's data lab query, and the search word was 'induced abortion' in Korean. The average trend of each year was analyzed and the seasonality was analyzed using the cosinor model. Results: There was no significant changes in search volume of abortion during that period. Monthly search volume was the highest in May followed by the order of June and April. On the other hand, the lowest month was December followed by the order of January, and September. The cosinor analysis showed statistically significant seasonal variations (amplitude, 4.46; confidence interval, 1.46-7.47; p< 0.0036). The search volume for induced abortion gradually increased to the lowest point at the end of November and was the highest at the end of May and declined again from June. Conclusion: There has been no significant changes in induced abortion for the past nine years, and seasonal changes in induced abortion have been identified. Therefore, considering the seasonality of the intervention program for the prevention of induced abortion, it will be effective to concentrate on the induced abortion from March to May.

A Study on Subscriber's Preference Factors through Korea, United States and Japan Webtoon Data Analysis : With Naver Webtoon (한, 미, 일 웹툰 분석을 통한 구독자 선호 요인 탐색 : 네이버 웹툰을 중심으로)

  • Do, Sang-Beum;Kang, Juyoung
    • The Journal of Bigdata
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    • v.3 no.1
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    • pp.21-32
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    • 2018
  • Currently, Webtoon Industry is promising as high potential market from it's high growth trend. The best advantage webtoon propose is that webtoon can provide appropriate service to customers with various needs. For this feature, webtoon industry is expanding throughout the world. This situation may give a great chance for authors and webtoon service corporation to export webtoon contents. Also, this situation could be an opportunity for webtoon to become a new "Korean Wave" contents. For successful advance to market, a close analysis for customers of exporting countries. In this research, we collected the data from Naver Webtoon and analyzed the features of webtoons and webtoon subscribers according to countries. With this research, it would be possible to find out specific methods and variables which affect the preference of webtoon subscribers.

A Comparative Study of Consumer's Hype Cycles Using Web Search Traffic of Naver and Google (웹 검색트래픽을 활용한 소비자의 기대주기 비교 연구: 네이버와 구글 검색을 중심으로)

  • Jun, Seung-Pyo;Kim, You Eil;Yoo, Hyoung Sun
    • Journal of Korea Technology Innovation Society
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    • v.16 no.4
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    • pp.1109-1133
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    • 2013
  • In an effort to discover new technologies and to forecast social changes of technologies, a number of technology life-cycle models have been developed and employed. The hype cycle, a graphical tool developed by a consulting firm, Gartner, is one of the most widely used models for the purpose and it is recognised as a practical one. However, more research is needed on theoretical frames, relations and empirical practices of the model. In this study, hype cycle comparisons in Korean and global search websites were performed by means of web-search traffic which is proposed as an empirical measurement of public expectation, analysed in a specific product or country in previous researches. First, search traffic and market share for new cars were compared in Korea and the U.S. with a view to identifying differences between the hype cycles in the two countries about the same product. The results show the similarity between the two countries with the statistical significance. Next, comparative analysis between search traffic and supply rate for several products in Korea was conducted to check out their patterns. According to the analysis, all the products seem to be at the "Peak of inflated expectations" in the hype cycles and they are similar to one another in the hype cycle. This study is of significance in aspects of expanding the scope of hype cycle analysis with web-search traffic because it introduced domestic web-search traffic analysis from Naver to analyse consumers' expectations in Korea by comparison with that from Google in other countries. In addition, this research can help to explain social phenomina more persuasively with search traffic and to give scientific objectivity to the hype cycle model. Furthermore, it can contribute to developing strategies of companies, such as marketing strategy.

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The Development of Travel Demand Nowcasting Model Based on Travelers' Attention: Focusing on Web Search Traffic Information (여행자 관심 기반 스마트 여행 수요 예측 모형 개발: 웹검색 트래픽 정보를 중심으로)

  • Park, Do-Hyung
    • The Journal of Information Systems
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    • v.26 no.3
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    • pp.171-185
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    • 2017
  • Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

A study on custom Hanbok design through on-line review - From 2016 To 2017 - (온라인 후기를 통한 맞춤 웨딩한복의 디자인 고찰 2016년~2017년)

  • Ryu, Kyoung-ok
    • Journal of the Korea Fashion and Costume Design Association
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    • v.20 no.3
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    • pp.27-32
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    • 2018
  • Hanbok is a our own history and tradition and is an icon of Korean history and culture. Today, the costumes are moving around the world fashion trend due to the development of mass media and internet at the same time. This is an important clue to marketing activities and can be used for predictive analysis. Although Hanbok is changing little by little every year, research on the trend of Hanbok is rare. This study analyzed the results of searching for 'Hanbok' as a keyword in Portal Site Naver and posting a customized purchase of Hanbok for marriage between 2016 and 2017. The analysis was based on analyzing the photos uploaded, and analyzing purchase reason in the On-line review. Most buyer of Hanbok purchased for prepare marriage. The choice of a customized hanbok is mostly to search online or to use the fair. The most important factor in choosing a custom Hanbok that appeared in online reviews is color and then price. The color of the jacket is mostly light color and the off-white color is the most used and the long skirt such as the pink system, the chorale system and the red system, and it can be seen that the pink skirt is overwhelmingly large. In the design of Hanbok, The sleeves were straight and narrow, and the length was the chest line. The collar were enlarged and widened. 고름 used the sole color instead of the jacket and skirt color, and it was narrow not long. skirt's pleats was wide, and designed to overlap with double color of the fabric.

Necessity of Adverse Event Reporting System through the Trend of Internet News about Safety of Herbal Medicine (한약의 안전성에 대한 인터넷 보도의 특성을 통해 본 한약 부작용 관리 체계 확립의 필요성)

  • Cheon, Chun-Hoo;Park, Jeong-Su;Park, Sun-Ju;Kweon, Kee-Tae;Shin, Yong-Cheol;Ko, Seong-Gyu
    • Journal of Society of Preventive Korean Medicine
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    • v.15 no.2
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    • pp.131-143
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    • 2011
  • Objective : The aims of this study are to investigate the trend of internet journalism about the toxicity and safety of the herbal medicine, and to suggest the regulatory solution of the issue. Method : In this study, we had searched the internet news article published from 2001 to 2011 in the five major portal sites-NAVER, DAUM, Nate, Google Korean, and Yahoo Korean. The search terms were 'herbal medicine', 'adverse event', 'toxicity'. If the articles described the same event in the same form and tone, the articles were considered overlapping. The overlapped articles were excluded. The articles were categorized by the form and tone. The form categories were straight news, interpretative story, editorial, interview, and the tone categories are the positive, the negative, and the neutral. The regulations were searched about the negative issue. Result : Total 56 articles were reviewed. There were 19 positive articles, 29 negative articles, 8 neutral articles. Most negative issues have the proper regulations, but insufficient measures for the adverse event reporting system. Conclusion : The herbal medicine specified adverse event reporting system is essential.

Domestic Research Trend of Internet of Things based on Keyword Frequency and Centrality Analysis (키워드 빈도와 중심성 분석에 기반한 사물인터넷 국내 연구 동향)

  • Lee, Taekkyeun
    • The Journal of the Korea Contents Association
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    • v.20 no.12
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    • pp.23-35
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    • 2020
  • This study aims to examine trends in the IoT field by collecting and analyzing domestic papers on IoT that will have a great impact across industries and society. The survey period for this study was from 2015 to 2019, and the domestic papers on the IoT were collected using Naver's Academic Information. We extracted the keywords with high frequency from the domestic papers collected by the period and performed the centrality analysis to identify the central keywords among the keywords with high frequency. In terms of keyword frequency, 'sensor' and 'security' from 2015 to 2017 appeared as the top keywords with high frequency. From 2017, 'car' and 'intelligence' appeared as the top keywords with high frequency. In terms of keyword centrality, 'security' and 'sensor' from 2015 to 2016 appeared as highly centralized keywords. From 2017, 'intelligence', 'car' and 'industrial revolution' appeared as highly centralized keywords.

A Trend Analysis of Floral Products and Services Using Big Data of Social Networking Services

  • Park, Sin Young;Oh, Wook
    • Journal of People, Plants, and Environment
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    • v.22 no.5
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    • pp.455-466
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    • 2019
  • This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.