LEADER 03672nam 2200457 450 001 9910483959803321 005 20210218225956.0 010 $a981-15-7376-X 024 7 $a10.1007/978-981-15-7376-7 035 $a(CKB)4100000011469534 035 $a(MiAaPQ)EBC6355537 035 $a(DE-He213)978-981-15-7376-7 035 $a(EXLCZ)994100000011469534 100 $a20210218d2020 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIndividual retweeting behavior on social networking sites $ea study on individual information disseminating behavior on social networking sites /$fJuan Shi, Kin Keung Lai, Gang Chen 205 $a1st ed. 2020. 210 1$aGateway East, Singapore :$cSpringer,$d[2020] 210 4$dİ2020 215 $a1 online resource (XVII, 132 p. 38 illus., 20 illus. in color.) 311 $a981-15-7375-1 327 $a1. Introduction -- 2. Research Background and Research Questions -- 3. Literature Review and Theoretical Foundation -- 4. Research Scheme Design -- 5. Dominating Factors Affecting Individual Retweeting Behavior -- 6. Direct Effect and Mediating Effect of Individual Retweeting Behavior on SNS -- 7. Moderating Effect of Individual Retweeting Behavior on SNS -- 8. Conclusion and Discussion. 330 $aThis 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. 606 $aOnline social networks$xPsychological aspects 608 $aElectronic books. 615 0$aOnline social networks$xPsychological aspects. 676 $a302.30285 700 $aZhang$b Shihua$0966488 702 $aLai$b Kin Keung 702 $aChen$b Gang 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483959803321 996 $aIndividual retweeting behavior on social networking sites$92193457 997 $aUNINA