Examining the power-law distribution among eWOM communities: a characterisation approach of the Long Tail

ABSTRACT

Nowadays electronic word-of-mouth (eWOM) communities symbolise a significant source of information that helps customers to make informed purchasing decisions. Through eWOM communities, a great audience of users is able to acquire knowledge from reviews concerning products and services that are less popular to the majority. The Long Tail effect is a manifestation of such redistribution of demand from popular products to niche products. In this paper, a new methodology that mathematically fits the relationship between the power-law distribution and the Long Tail from an eWOM community is developed. In addition, this paper defines a tool for finding niche products inaccessible through conventional channels. The results are consistent in showing that not all the categories fitting a power-law distribution are characterised by the Long Tail phenomenon, and conversely some of those having a Long Tail do not fit a power-law distribution.

KEYWORDS:

• eWOM
• online user reviews
• power-law distribution
• Long Tail theory
• product categorisation

Notes on contributors

M. Olmedilla is a doctoral student at the Business Administration and Marketing Department, University of Seville. Her research involves the study of eWOM communities and social network analysis.

María del Rocío Martínez-Torres is an Associate Professor in Management and Business Administration at Business Administration and Marketing Department, University of Seville. Her main research interests include Intellectual Capital and Knowledge Management, Social Network Analysis, Open Innovation and Virtual Communities. She has co-authored articles in many leading academic and professional journals, including: Information and Management; IEEE Transactions on Education; Computers & Education; and Behaviour and Information Technology.

Sergio Toral is an Associate Professor in Digital Electronic Systems at the Department of Electronic Engineering, University of Seville. His main research interests include Open Source Software projects, Open Innovation and Social Network Analysis.

ORCID

M. Martínez-Torres http://orcid.org/0000-0002-1640-0020

S. L. Toral http://orcid.org/0000-0003-2612-0388

Additional information

Funding

This work was supported by the Consejería de Economía, Innovación, Ciencia y Empleo under the Research Project with reference P12-SEJ-328, and by the Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad under the Research Project with reference ECO2013-43856-R.