초록

본 연구는 높은 접근성과 간결성으로 인해 방대한 양의 텍스트를 생산하는 트위터 데이터를 분석하여 토픽의 변화 시점 및 패턴을 파악하였다. 먼저 특정 상품명에 관한 키워드를 추출한 후, 동시출현단어분석(Co-word Analysis)을 이용하여 노드와 에지를 통해 토픽과 관련 키워드를 직관적으로 파악 가능한 네트워크로 표현하였다. 이후 네트워크 분석 결과를 검증하기 위해 출현빈도 기반의 시계열 분석과 LDA 토픽 모델링을 실시하였다. 또한 트위터 상의 토픽 변화와 언론 기사 검색결과를 비교한 결과, 트위터는 언론 뉴스에 즉각적으로 반응하며 부정적 이슈를 빠르게 확산시키는 것을 확인하였다. 이를 통해 기업은 대중의 부정적 의견을 신속하게 파악하고 이에 대한 즉각적인 의사결정 및 대응을 위한 도구로 본 연구방법을 활용할 수 있을 것으로 기대된다.

Abstract

This study identified topic shifts and patterns over time by analyzing an enormous amount of Twitter data whose characteristics are high accessibility and briefness. First, we extracted keywords for a certain product and used them for representing the topic network allows for intuitive understanding of keywords associated with topics by nodes and edges by co-word analysis. We conducted temporal analysis of term co-occurrence as well as topic modeling to examine the results of network analysis. In addition, the results of comparing topic shifts on Twitter with the corresponding retrieval results from newspapers confirm that Twitter makes immediate responses to news media and spreads the negative issues out quickly. Our findings may suggest that companies utilize the proposed technique to identify public’s negative opinions as quickly as possible and to apply for the timely decision making and effective responses to their customers.

초록

Abstract

Even though the overall scholarly community has recognized a dramatic growth and changes in the Information Science research in Korea over the last few decades, there are still only few studies that have identified the changes in terms of long-term and dynamic point of view. We have analyzed 1,007 IS-research articles from leading Korean journals in KCI (Korea Citation Index), published between 2000 and 2011. To discern the trendline of changes in research interests over time, we conducted a time-series analysis by developing grounded subject scheme from the article set and checking the growth rate of the number of published articles and title keywords. A comparative analysis was also conducted by constructing and comparing co-word maps over time to discover visible changes in research topics over this 12-year period of the IS-research in Korea. As a result, we identified some developments and transformations in major subject areas and knowledge structure of the IS-research in Korea over time. The major trend we discovered is that IS-studies over the 12-year period evolved from system-oriented research to library-application research. The changes are especially observed in knowledge management, Web-based system evaluation, and information retrieval areas. When compared to the results of other studies, the result of our study may serve as an evidence of the localization of Korean IS-studies in the first decade of the 21st century.