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Analysis of Research Trends of ‘Word of Mouth (WoM)’ through Main Path and Word Co-occurrence Network
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Hyunbo Shin (Graduate School of Information, Yonsei University)
Hea-Jin Kim (Department of Library and Information Science Education, Kongju National University)
Vol. 25, No. 3, Page: 179 ~ 200
Keywords
Citation Analysis, Keyword Co-occurrence Network, Main Path Analysis, Meta Analysis, Word-of-Mouth (WoM), Text Mining
Abstract
Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information.
Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction.
To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes.
However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM.
By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words.
This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.
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주경로 분석과 연관어 네트워크 분석을 통한 ‘구전(WoM)’ 관련 연구동향 분석
신현보 (연세대학교 정보대학원)
김혜진 (국립공주대학교 사범대학 문헌정보교육과)
Keywords
구전, 메타분석, 인용분석, 연관어 네트워크, 주경로 분석, 텍스트 마이닝
Abstract
구전(Word-of-Mouth) 활동은 오래 전부터 기업의 마케팅 과정에서 중요성을 인식하고 특히 마케팅 분야에서많은 주목을 받아왔다. 최근에는 인터넷의 발달에 따라 온라인 뉴스, 온라인 커뮤니티 등에서 사람들이 지식과정보를 주고 받는 방식이 다양해지면서 구전은 후기, 평점, 좋아요 등으로 입소문의 양상이 다각화되고 있다.
이러한 현상에 따라 구전에 관한 다양한 연구들이 선행되어왔으나, 이들을 종합적으로 분석한 메타 분석 연구는 부재하다. 본 연구는 학술 빅데이터를 활용해 구전 관련 연구동향을 알아내기 위해서 텍스트 마이닝 기법을적용하여 주요 연구들을 추출하고 시기별로 연구들의 주요 쟁점을 파악하는 기법을 제안하였다. 이를 위해서1941년부터 2018년까지 인용 데이터베이스인 Scopus에서 ‘Word-of-Mouth’라는 키워드로 검색되는 총 4389건의문헌을 수집하였고, 영어 형태소 분석과 불용어 제거 등 전처리 과정을 통해 데이터를 정제하였다. 본 연구는학문 분야의 발전 궤적을 추적하는 데 활용되는 주경로 분석기법을 적용해 구전과 관련된 핵심 연구들을 추출하여 연구동향을 거시적 관점에서 제시하였고, 단어동시출현 정보를 추출하여 키워드 간 네트워크를 구축하여시기별로 구전과 관련된 연관어들이 어떻게 변화되었는지 살펴봄으로써 연구동향을 미시적 관점에서 제시하였다. 수집된 문헌 데이터를 기반으로 인용 네트워크를 구축하고 SPC 가중치를 적용하여 키루트 주경로를 추출한 결과 30개의 문헌으로 구성된 주경로가 추출되었고, 연관어 네트워크 분석을 통해서는 시기별로 온라인 시대, 관광 산업 등 다양한 산업군 등 산업 변화가 반영돼 시대적 변화와 더불어 발전하고 있는 학술적 영역의변화를 확인할 수 있었다.
Cite this article
JIIS Style
Shin, H., and H.-J. Kim, "Analysis of Research Trends of ‘Word of Mouth (WoM)’ through Main Path and Word Co-occurrence Network", Journal of Intelligence and Information Systems, Vol. 25, No. 3 (2019), 179~200.

IEEE Style
Hyunbo Shin, and Hea-Jin Kim, "Analysis of Research Trends of ‘Word of Mouth (WoM)’ through Main Path and Word Co-occurrence Network", Journal of Intelligence and Information Systems, vol. 25, no. 3, pp. 179~200, 2019.

ACM Style
Shin, H., and Kim, H.-J., 2019. Analysis of Research Trends of ‘Word of Mouth (WoM)’ through Main Path and Word Co-occurrence Network. Journal of Intelligence and Information Systems. 25, 3, 179--200.
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@article{Shin:JIIS:2019:787,
author = {Shin, Hyunbo and Kim, Hea-Jin},
title = {Analysis of Research Trends of ‘Word of Mouth (WoM)’ through Main Path and Word Co-occurrence Network},
journal = {Journal of Intelligence and Information Systems},
issue_date = {September 2019},
volume = {25},
number = {3},
month = Sep,
year = {2019},
issn = {2288-4866},
pages = {179--200},
url = {},
doi = {},
publisher = {Korea Intelligent Information System Society},
address = {Seoul, Republic of Korea},
keywords = { Citation Analysis, Keyword Co-occurrence Network, Main Path Analysis, Meta Analysis, Word-of-Mouth (WoM) and Text Mining
},
}
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%A Hea-Jin Kim
%T Analysis of Research Trends of ‘Word of Mouth (WoM)’ through Main Path and Word Co-occurrence Network
%J Journal of Intelligence and Information Systems
%@ 2288-4866
%V 25
%N 3
%P 179-200
%D 2019
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%I Korea Intelligent Information System Society