TY - BOOK ID - 65545631 TI - Individual retweeting behavior on social networking sites : a study on individual information disseminating behavior on social networking sites AU - Zhang, Shihua AU - Lai, Kin Keung AU - Chen, Gang PY - 2020 SN - 981157376X 9811573751 PB - Springer Singapore DB - UniCat KW - Social media. KW - Psychology. KW - Social Media. KW - Psychology, general. KW - Behavioral sciences KW - Mental philosophy KW - Mind KW - Science, Mental KW - Human biology KW - Philosophy KW - Soul KW - Mental health KW - User-generated media KW - Communication KW - User-generated content KW - Online social networks KW - Psychological aspects. KW - Electronic social networks KW - Social networking Web sites KW - Virtual communities KW - Social media KW - Social networks KW - Sociotechnical systems KW - Web sites KW - Communities, Online (Online social networks) KW - Communities, Virtual (Online social networks) KW - Online communities (Online social networks) UR - https://www.unicat.be/uniCat?func=search&query=sysid:65545631 AB - This book explores and analyzes influential predictors and the underlying mechanisms of individual content sharing/retweeting behavior on social networking sites (SNS) from an empirical perspective. Since Individual content sharing/ retweeting behavior expedites information dissemination, it is a critical mechanism of information diffusion on Twitter. Individual sharing/retweeting behavior does not appear to happen randomly. So, what factors lead to individual information dissemination behavior? What are the dominating predictors? How does the recipient make retweeting decisions? How do these influential predictors combine and by what mechanism do they influence an individual’s retweeting decisions? Furthermore, are there any differences in the process of individual retweeting decisions? If so, what causes such differences? In order to answer these previously unexplored questions and gain a holistic view of individual retweeting behavior, the authors examined people’s retweeting history on Twitter and obtained a real dataset containing more than 60 million Twitter posts. They then employed text mining and natural language processing techniques to extract useful information from social media content, and used various feature selection methods to identify a subset of salient features that have substantial effects on individual retweeting behavior. Lastly, they applied the Elaboration Likelihood Model to build an overarching theoretical framework to reveal the underlying mechanisms of individual retweeting behavior. Given its scope, this book will appeal to researchers interested in investigating information dissemination on social media, as well as to marketers and administrators who plan to use social networking sites as an important avenue for information dissemination. ER -