[EN]Purpose – Due to the size and importance of social media, user-generated content analysis is becoming a key
factor for companies and brands across the world. By using Twitter messages’ content, the purpose of this
paper is to identify which elements of the messages enable tweet diffusion and facilitate eWOM.
Design/methodology/approach – In total, 30,082 tweets collected from 10,120 Twitter users were
classified based on four assorted brands. By comparing with multiple regression techniques high vs low
purchase involvement and hedonic vs utilitarian products and using the theory of heuristic-systematic
processing of information, the authors examine the causes of tweet diffusion.
Findings – The authors illustrate how the elements of a tweet (hashtags, mentions, links, sentiment or tweet
length) influence its diffusion and popularity.
Research limitations/implications – This study validated the use of information processing theories in
the social media field. The study showed a picture on how different Twitter elements influence eWOM and
message diffusion under several purchase involvement situations.
Practical implications – The results of this study can help social media brand community managers of all
types of companies on how to write their Twitter messages to obtain greater dissemination and popularity.
Originality/value – The study offers a unique deep brand analysis which helps brands and companies to
understand their social media popularity in detail. Depending on product category, companies can achieve
maximum social impact
