Analysis of research papers on E-commerce (2000–2013): based on a text mining approach

Abstract

E-commerce (EC) is sweep across the globe and has become a most important commercial activity. Accordingly, EC also causes the academia's research interests. A lot of research achievements have been gained in recent years. This paper takes these achievements as research object and collects 8488 research papers published in academic journals during 2000-2013 included in Web of Science database. Using text mining techniques, 68 terms are identified as the main keywords of EC field. Then the scientific structure of the EC is mapped through multidimensional scaling, based upon the cooccurrence of the main terms in the academic journals. The results show that the EC domain is composed of three main fields, such as technology, management and customer. Furthermore, knowledge graph based on the EC research network is visualized and it shows that the whole EC research papers covering seven important subnets, which are: internet, consumer behaviour, customer satisfaction, online shopping, reputation, Taiwan and knowledge management.

Business model analytics: technically review business model research domain

“…In addition, the high volume of texts in a research domain (e.g. the domain of business model) implicitly indicates the justification for using systematic and relatively hands-off approaches for review, organizing and summarization (Yan et al, 2015), especially when the field underdiscussion is interdisciplinary or multidisciplinary (Nerur et al, 2008). Therefore, first, this study aimed at using various and promising text mining techniques in an unprecedented manner within the business model field of study to overcome the limitations of conventional qualitative methods and simultaneously gain the advantages of novel quantitative analyses.…”

“…3.3.1 Co-word analysis. Co-word analysis as one of the text mining methods was first proposed by Callon et al (1983) (Yan et al, 2015). This technique is based on the main idea that co-occurrence of important words describes the relation between the contents of a specific set of documents (Callon et al, 1991).…”

“…In this study, the VOSviewer software has been used to visualize the results of co-word analysis and to draw the co-occurrence network of keywords. To draw this network, from among all keywords, including author keywords and Keywords Plus, the most iterative keywords were detected using the frequency g-index method (Yan et al, 2015). According to the discussion provided by Van Eck and Waltman (2014), visualization in the VOSviewer software is done based on the distance-based approach.…”

A Survey of Text Mining in Social Media: Facebook and Twitter Perspectives

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Information gain in alternative data: Evidence from e‐commerce sales and analyst earnings forecasts

“…E‐commerce is sweeping across the globe and has become an important commercial activity under the booming digital economy (Yan et al, 2015). Compared with other alternative data, firms' e‐commerce sales data can be obtained directly from consumers' purchasing behaviors.…”