How can trustworthy influencers be identified in electronic word-of-mouth communities?

Abstract

Given eWOM's growing importance and the interest of companies in having their products positively rated, it is necessary to analyze the behavior of influencers in online communities and determine the activities that might explain their level of trustworthiness. This paper focuses on identifying the different attributes obtained from online communities’ system-generated profiles to consider trustworthy reviewers. A structural equation model has been developed to measure trustworthiness as a construct, using the peer-nominated approach and a variety of indicators. Findings reveal a range of behavior patterns that can identify influencers based on their trustworthiness. A reviewer's involvement and sociability have strong relationships with the trust that he/she evokes in other users. Actions such posting reviews, scoring other members’ reviews and adding them to his/her trust network have a great relationship with trustworthiness. Also, a reviewer's specialization and experience have significant, although weaker, relationships with his/her level of trustworthiness. This research makes significant managerial contributions in detecting the most trustworthy and influential reviewers, and their characteristic actions to focus their use of viral marketing techniques on this subset of users with the aim of sparking interest in certain products in a faster, more credible and more efficient way in terms of costs.