• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.79-97
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• 2014

This study was to evaluate the quality of academic information services provided by Naver Academic Information Service, Google Scholar, and MS Academic Search. This academic information services were evaluated in terms of the contents, service, and effectiveness. 135 four year college students were recruited for the survey. The results showed that the Google Scholar in contents section had higher score than Naver and MS Academic Search. In regard to service, Google Scholar had higher score in retrieval section while Naver had higher score in design section respectively. Finally, both Google Scholar and Naver in the access section had higher score than MS Academic Search.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.2
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• pp.255-279
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• 2017

In a qualitative approach, this study investigated users' perceptions associated with their satisfactions in the process of using the scholarly resource search functions of the academic version of the NAVER search engine. For this study, the data was collected from a group of undergraduate students, who conducted academic information searches in the field of own major disciplinary areas, using the Web portal. Based on the data, students' satisfactions and dissatisfactions along with the reasons of their perceptions were analyzed. The results presented users' perceptions in various evaluation criteria based on the three major domains: system interfaces, retrieval mechanisms and search results. Based on the results, the study proposed the following suggestions: 1) the enhancements of the system interfaces and HELP guidances based the limited user knowledge on basic system terminologies 2) the improvements of the retrieval mechanisms associated with understanding the contexts of the search terms presented by users 3) the necessity of the user education due to the insufficient user knowledge of the retrieval mechanisms and the search functions.

• Journal of Information Management
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• v.36 no.4
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• pp.71-89
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• 2005

This paper examines the ways of using information resources available through information retrieval systems of portal sites. We analyze the types of information resources, search capabilities, and interfaces of Naver, Empas, and Google Scholar. Naver's retrieval system sells research reports, papers, patents information, etc. to users, which is similar to C2C(Customer to Customer in e-commerce environment). Empas provides information from journals, research reports, and proceedings with no charge. Google Scholar's noteworthy efforts are their collaborative programs with and/or for major U.S. libraries, such as "Library Link" and "Library Project." Considering the extended information retrieval services of portals, especially the services like Google Scholar's library programs, libraries need to develop more specialized services, such as the customized information service for individual user, development of user convenience tools like OCLC WorldCat, more accessibility through ubiquitous library concept, and collaboration among libraries.

• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.297-315
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• 2013

This study aims to analyze and evaluate term suggestion services of major search portals, Naver and Google Korea. In particular, this study evaluated relevance and currency of related search terms provided, and analyzed characteristics such as number and distribution of terms, and queries that did not produce terms. This study also analyzed types of terms in terms of the relationship between queries and terms, and investigated types and characteristics of harmful terms and terms with grammatical errors. Finally, Korean queries and English queries, and popular queries and academic queries were compared in terms of the amount and relevance of search terms provided. The results of this study show that the relevance and currency of Naver's related search terms are somewhat higher than those of Google. Both Naver and Google tend to add terms to or delete terms from original queries, and provide identical search terms or synonym terms rather than providing entirely new search terms. The results of this study can be implemented to the portal's effective development of term suggestion services.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.116-125
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• 2022

The purpose of this study is to analyze whether investor anxiety caused by COVID-19 affects cryptocurrency prices in the COVID-19 pandemic, and to experiment with cryptocurrency price prediction based on a deep learning model. Investor anxiety is calculated by combining Naver's Corona search index and Corona confirmed information, analyzing Granger causality with cryptocurrency prices, and predicting cryptocurrency prices using deep learning models. The experimental results are as follows. First, CCI indicators showed significant Granger causality in the returns of Bitcoin, Ethereum, and Lightcoin. Second, LSTM with CCI as an input variable showed high predictive performance. Third, Bitcoin's price prediction performance was the highest in comparison between cryptocurrencies. This study is of academic significance in that it is the first attempt to analyze the relationship between Naver's Corona search information and cryptocurrency prices in the Corona phase. In future studies, extended studies into various deep learning models are needed to increase price prediction accuracy.

• Journal of The Korean Association of Information Education
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• v.20 no.1
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• pp.29-38
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• 2016

This study selected and utilized the 'Naver post' as an e-book production tool to be used for learning. The production of such SNS format e-books aimed at founding out its effect on learning attitude and academic achievement by stimulating interest and confidence in the learning of the students. To accomplish such an aim, the study selected 50 students from two classes in the fourth grade of a public elementary school. One class of 25 students went through a social studies lesson that applied SNS type e-book production activities, and the other class of 25 students underwent a regular social studies lesson as the comparative group. The major results of the study's analysis is SNS type e-book production did not significantly improve academic achievement in social studies, but SNS type e-book production significantly improved the learning attitude during social studies.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.181-196
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• 2016

The objective of this study is to evaluate the organization system and the labeling system of information architecture of a website for the elderly. To achieve this aims, we selected a representative website, i.e., Naver, and the participants were conducted given three types of search tasks using their own information literacy skills and they were answered to the questionnaire and an additional interview, if necessary. A total of 74 valid data were collected through the experiment, and we analyzed the data using SPSS Ver. 20. It revealed that Naver received a positive evaluation in the organization system aspect, particularly its systematic subject categorization and chronological browsing mechanisms. Old adults were preferred the icon-based labeling than the text-based labeling system, and showed a significant difference among their academic backgrounds.

• 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.

• Informatization Policy
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• v.25 no.4
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• pp.37-64
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• 2018

This study aims to forecast the future of the Korean society via a big data analysis. Based upon two sets of database - a collection of 46,000,000 news on 127 media in Naver Portal operated by Naver Corporation and a collection of 70,000 academic papers of social sciences registered in KCI (Korea Citation Index of National Research Foundation) between 2005-2017, 40 most frequently occurring keywords were selected. Next, their temporal variations were traced and compared in terms of number and pattern of frequencies. In addition, core issues of the future were identified through keyword network analysis. In the case of the media news database, such issues as economy, polity or technology turned out to be the top ranked ones. As to the academic paper database, however, top ranking issues are those of feeling, working or living. Referring to the system and life-world conceptual framework suggested by $J{\ddot{u}}rgen$ Habermas, public interest of the future inclines to the matter of 'system' while professional interest of the future leans to that of 'life-world.' Given the disparity of future interest, a 'mismatch paradigm' is proposed as an alternative to social forecasting, which can substitute the existing paradigms based on the ideas of deficiency or deprivation.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.1
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• pp.47-65
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• 2022

This study investigated college students' demand for academic information portals and conducted an improvement plan to help ScienceON become an eco-friendly portal for college students. To this end, an academic information portal similar to ScienceON was investigated and analyzed, and FGI interviews were conducted with college students to derive improvements based on the problems ScienceON felt by college students. The improvement measures proposed based on the research results are as follows. First, it is necessary to strengthen the integrated search function and instill confidence that college students can obtain all the information they want from ScienceON. Second, it is necessary to have UIs such as Google and Naver, which are preferred by college students, and improve the current hard design. Third, it is necessary to make ScienceON familiar by promoting it targeting lower grades of the university. Currently, college students belong to the MZ generation, and the MZ generation is expected to become a generation that forms a social core in the future, and related research on the MZ generation is increasing. Therefore, this study can be used as basic data for research on MZ generation, and in particular, it seems that it can be used as a reference for the demand for information search and services of MZ generation.