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The purpose of this study is to investigate influencers on Twitter to discover the characteristics of their
tweets through PIAR, a unique data mining research tool developed by the University of Salamanca that
combines graph theory and social influence theory. An analysis of 3853 users posting about two auto-
motive Japanese car firms, Toyota and Nissan, reveals the characteristics influencers have on this social
network. The findings suggest that influencers use more hashtags and mentions on average when they
tweet, and their word count is fewer than those with less power on this virtual community. Surprisingly,
they tend to include less embedded links on their posts. Additionally, influencers have on average a large
number of people they follow and they clearly express their opinions and feelings (either positive or
negative) when tweeting. The results broaden the understanding of how influencers write and behave on
social networks when they communicate with their users' community. Further, it provides insights for
practitioners and marketers on how to discover influencers talking about their brands by observing
tweets' content.
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