빅데이터를 활용한 템플스테이 트렌드 분석

양택수,김진한 사단법인한국교수불자연합회 2020 한국교수불자연합학회지 Vol.26 No.2

The purpose of this study is to understand Templestay trends through big data analysis. We use the language maps using 'Some Trend' provided by Daumsoft as a method of text mining for eliciting research results. And we analyze the trend of newspaper articles through 'Big Kinds' by Korea Press Foundation. Finally, 'Google Trends' and 'Naver DataLab' were used to analyze the Internet search results of Templestay. Study shows that first, Templestay is perceived as a positive image. Second, newspaper articles on Templestay have been on a steady rise since the introduction of Templestay, and the most frequently mentioned words are "Buddhism" (185 times), "Foreigner" (82 times), "Buddhist Culture" (79 times), "Geumsansa Temple" (44 times), and "Varugongyang" (42). Third, the four-year Templestay search results since 2016 show a tendency in increase of the search volume in mid-March, mid-June and mid-September. Finally, the number of Templestay visitors steadily increase from Spring to Summer to reach a peak and declines from Fall to Winter. Through this study, it is expected that big data analysis will be used as a basic source of marketing to promote Templestay and to predict future trends of Templestay. 본 연구의 목적은 빅데이터 분석을 통해 템플스테이 트렌드를 이해하는데 있다. 연구결과 도출을 위하여 다음소프트에서 제공하는 텍스트 마이닝(text mining) 분석도구인썸드렌트(Some Trend)를 이용하여 연관어 맵을 작성하고 이를 통해 감성, 긍정·중립·부정 반응 및 추이를 분석했다. 그리고 한국언론진흥재단에서 제공하는 빅카인즈(B ig Kinds)를 이용하여 신문기사에서 템플스테이 관련 언급추이를 분석하였다. 마지막으로 구글 트렌드(Google Trends)와 네이버 데이터랩(Naver Datalab)을 활용하여 템플스테이에 대한 인터넷 검색 엔진의 검색량과 추이를 분석했다. 연구결과 첫째, 템플스테이는 긍정적인 이미지로 인식되고 있는 것으로 나타났다. 둘째, 템플스테이 관련 신문기사는 템플스테이 시행 이후 꾸준한 증가세를 보이고 있으며, 가장 많이 언급된 단어는 ‘불교’(185회), ‘외국인’(82회), ‘불교문화’(79회), ‘금산사’ (44회), ‘발우공양’(42회) 순으로 나타났다. 셋째, 2016년 이후 4년간 템플스테이의 검색량 추이를 확인 한 결과 3월 중순, 6월 중순, 9월 중순에 검색량이 증가하는 경향을보이고 있다. 마지막으로 템플스테이 참가자는 봄부터 여름까지 증가하는 경향을 보이다 정점을 찍은 후 가을부터 겨울까지는 감소하는 경향을 보이는 것으로 나타났다. 본연구를 통해 템플스테이의 미래 트렌드에 대한 예측을 할 수 있고, 향후 템플스테이 활성화를 위한 마케팅 기본 자료로 활용되기를 기대한다.

여행자 관심 기반 스마트 여행 수요 예측 모형 개발: 웹검색 트래픽 정보를 중심으로

박도형 ( Park Do-hyung ) 한국정보시스템학회 2017 情報시스템硏究 Vol.26 No.3

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.

사회적기업 인식에 관한 연구: 네이버 트렌드 데이터를 활용하여

이현진,이승우 사단법인 사회적기업학회 2018 사회적기업연구 Vol.11 No.1

본 연구는 네이버 트렌드에서 추출한 빅데이터를 활용하여 사회적기업에 대한 학문적, 실무적 시사점을 도출하는 것을 목표로 한다. 이를 위해 일자리 문제와 사회적기업 간 상관관계와 인과관계를 검정한다. 구체적으로 총 5개의 가설을 통하여 정부 차원에서 이루어진 사회적기업의 육성이 사람들의 마음속에 일자리 문제 해결의 주체 혹은 일자리 문제에 관한 관심을 촉구하는 매개체의 역할을 하는지 살펴본다. 일자리 문제 키워드는 선행연구 등을 토대로 하여 구직, 구직난, 일자리, 취업, 취업난, 취직, 취직난의 총7개 키워드를 선정하였다. 각각의 키워드에는 사회적기업 육성법 제2조에서 정의하고 있는 취약계층의 범위를 하위 검색어로 입력하였다. 분석 결과, 일자리 문제와 사회적기업에 관한 관심의 상관관계는 유의한 정(+)의 관계가 있는 것으로 나타났다. 일자리 문제에 관한 관심은 사회적기업에 관한 관심으로 이어지는 것으로 나타났다. 이를 통해 사회적기업의 사회문제 해결의 주체로서 해야 할 역할을 확인하였다. 그러나 사회적기업이 일자리 문제에 관한관심을 촉구하는지는 확인하지 못하였다. 또한, 성별과 연령대에 따라 관계의 강도 인식에 차이가 있는 것으로 나타났다. This paper analyses the relationship between social enterprises and jobcreation issues to discuss the academic and practical implications of SocialEnterprises by using big data extracted from Naver. Specifically, this study examines five hypotheses if the development of socialenterprises will play a role in the minds of potential consumers, as a means ofsolving social problems and promoting interest in job creation issues. Naver trends data was extracted for a certain period of time in specifickeywords. The keywords set is composed of employment, job seeking difficulty,employment, difficulty in finding employment, finding employment and findingemployment difficulty. As a result of the analysis, the role of social enterprises as the main actorsin solving job creation issues, but this study could not confirm whether socialenterprises are encouraging interest in job creation issues. In addition, thisstudy found that there was a difference in recognition of the strength of therelationship depending on gender and age.

네이버 데이터랩 검색어 트렌드 서비스를 이용한 온라인 포털에서의 한약재 검색 트렌드와 의미에 대한 고찰

김영식 ( Young-sik Kim ),이승호 ( Seungho Lee ) 대한본초학회 2021 大韓本草學會誌 Vol.36 No.5

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public's interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic. Methods : Using the “Naver DataLab (http://datalab.naver.com)” service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume. Results : ‘Cheonsangap (천산갑, 穿山甲, Manitis Squama)’ was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias. Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.

빅데이터로 알아보는 헤어, 뷰티 트렌드에 대한 연구 - 2021 F/W, 2022 S/S를 중심으로 -

안현경 한국뷰티경영학회 2023 한국뷰티경영학회지 Vol.11 No.1

In this study, to predict hair and beauty trend, used Naver Data Lab’s big data. Searching trends for one year that can be searched by category of Naver Data Lab and one for free searching terms that can be searched for 6 years from 2016 to 2022 were analyzed. The results of the beauty trend searching was as follows; The amount of clicks in the cosmetics/beauty field was on the rise. Among the beauty fields, the number of searches for nails was highest. The beauty industry was most interested in the Seoul. In the search volume for the beauty sector in Seoul, body shape management, general beauty, skin, and makeup showed a slight upward curve, while the hair industry a slight downward. The search interest in the beauty industry in Seoul was in the order of Gangnam-gu, Mapo-gu, Songpa-gu, and Seocho-gu. In Seoul, people used more cards hair than the skin/makeup sector, but for women in their over 50s and men in their over 60s, the card usage in the skin/makeup sector gradually exceeded that of the hair. In addition, men's hair field was dominate but women's hair field slightly higher than skin. The results of the hair trend searching was as follows; In the hair sector, search volume was increasing. Beauty salons searching ranking was in the order of Lian Hair, Tori Hair, Juno Hair, Lee Chul Hair Kerker, and ID Hair etc., and the amount of clicks on these were on the rise. The amount of clicks of professional scalp management salon was in the order of WT method, Dr. Scalp, and Welkin, but not increasing. Clicks in the hairstyle are gradually increasing. In many cases, they were searched by mobile, women, and in the 40s and 30s. Popular searching terms for hair styling was a lot of hair dye. The number of clicks of hair styling products was in order of hair wax, hair spray, dye, and perm drugs and it was gradually increasing. Clicks in the hair care sector are increasing, and popular searching terms are functional shampoos, essences, and oils. The aomount of click on hair care products are increasing slightly with shampoo, rinse, treatment, hair essence, and hair mist. Regional card usage for hair was in order of Seoul, Gyeonggi-do, and Busan.

소셜데이터 및 ARIMA 분석을 활용한 소비자 관점의 헬스케어 기술수요 예측 연구

양동원(Dong Won Yang),이준기(Zoon Ky Lee) 한국IT서비스학회 2020 한국IT서비스학회지 Vol.19 No.4

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as ARIMA (1,2,1) (1,0,0) , ARIMA (0,1,0) (1,0,0) , ARIMA (1,1,0) (0,0,0) . In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

웹 검색트래픽을 활용한 소비자의 기대주기 비교 연구

전승표(Seung-Pyo Jun),김유일(You Eil Kim),유형선(Hyoung Sun Yoo) 한국기술혁신학회 2013 기술혁신학회지 Vol.16 No.4

신기술을 발견하고, 사회적 변화를 예측ㆍ설명하기 위해 여러 가지 형태의 기술 수명주기 모델이 개발되어 활용되어 왔는데, 그 중에서 가트너(Gartner)사가 소개한 기술 기대주기(hype cycle) 이론은 현장에서 자주 활용되고 있으며 그 효과를 인정받고 있다. 그러나 널리 통용되는 인기에 비해서 현재 연구 문헌에서는 이론적 프레임과 관계 및 실증에 대한 고려가 부족했다. 본 연구에서는 이런 기대주기 모델의 새로운 실증적 측정 방법으로 제시된 웹 검색트래픽을 활용해 국내와 해외의 기대주기를 비교했다. 기존 연구에서 특정 제품이나 특정 국가에만 한정되었던 기대주기 분석을 검색트래픽을 활용해 비교 분석을 시도했다. 먼저 동일 제품에 대한 국가간 기대주기의 차이를 확인하기 위하여 검색트래픽과 신차판매점유율을 비교했는데, 국가간 기대주기의 유사성을 확인했으며, 통계적인 유의미성도 확인했다. 다음으로 동일 국간에서 제품간 기대주기의 차이를 확인하기 위하여 검색트래픽과 보급률을 비교해 보았는데, 역시 버블기의 정점 시기라는 측면에서 제품간 기대주기의 유사성도 확인했다. 본 연구는 검색트래픽을 활용한 사회현상 설명이나 기대주기 모델의 객관성과 설명력을 높이는데 크게 기여할 수 있으며, 나아가 마케팅 전략 수립과 같은 실질적인 기업전략 수립에까지 기여할 수 있을 것으로 판단된다. 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.

네이버 메인디자인 개편과 진행, 이후 국내 포털사이트들의 디자인 아이덴티티 구축을 위한 디자인의 변화와 영향

김거수 ( Ke Vin Kim ) 한국기초조형학회 2010 기초조형학연구 Vol.11 No.3

검색 포털을 이용한 미세먼지 관심과 여가활동 참여 관계 연구

조정형(Cho, Jeong-Hyung),김영재(Kim, Young-Jae) 한국체육과학회 2017 한국체육과학회지 Vol.26 No.4

As smartphone and Internet become widespread, everyone can search and obtain personal interests more easily. Therefore, this study aimed to examine the correlation between amounts of fine dusts in Seoul and the participation in the old palace in 2016 by using Naver trend offered by Naver Korean portal website. Data for 366 days was used for analysis. Closed days or under construction in the old palace were measured as missing values. First, analysis found that interests in fine dust was highest on April 24 and numbers of searching recorded the highest in May. Second, the highest amounts of fine dusts was recorded on April 23 and generally in spring. Third, a regression logic analysis of amounts of fine dust and interests in fine dust found that the higher amounts of fine dusts were, the more people paid attention. Fourth, the higher amounts of find dust and interests are, adult participants showed positive associations, while children participants showed negative association regarding the association between find dusts and old palace visitors. Lastly, the association between adult participants and children participants turned out positive. This study has its value in identifying the correlation between amounts of find dust, interests in find dust, and old palace participants. Based on these findings, more detailed research is needed in the following studies.

온라인 포털에서 한약재 검색 트렌드와 의미에 대한 고찰

이승호 ( Seung Ho Lee ),김안나 ( An Na Kim ),김상현 ( Sang Hyun Kim ),김상균 ( Sang Kyun Kim ),서진순 ( Jin Soon Seo ),장현철 ( Hyun Chul Jang ) 대한본초학회 2016 大韓本草學會誌 Vol.31 No.4

Objectives: The internet is the most common method to investigate information. It is showed that 75.2% of Internet users of 20s had health information search experience. So this study is aim to understanding of interest of public about the herbal medicine using internet search query volume data. Methods: The Naver that is the top internet portal web service of the Republic of Korea has provided an Internet search query volume data from January 2007 to the current through the Naver data lab (http://datalab.naver.com) service. We have collected search query volume data which was provided by the Naver in 606 herbal medicine names and sorted the data by peak and total search volume. Results: The most frequently searched herbal medicines which has less bias and sorted by peak search volume is ‘wasong (와송)’. And the most frequently searched herbal medicines which has less bias and sorted by total search volume is ‘hasuo (하수오)’. Conclustions: This study is showed that the rank of interest of public about herbal medicines. Among the above herbal medicines, some herbal medicines had supply issue. And there are some other herbal medicines that had very little demand in Korean medicine market, but highly interested public. So it is necessary to monitor for these herbal medicines which is highly interested of the public. Furthermore if the reliability of the data obtained on the basis of these studies, it is possible to be utilizing herbal medicine monitoring service.