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Individual retweeting behavior on so...

Chen, Gang.

Individual retweeting behavior on social networking sitesa study on individual information disseminating behavior on social networking sites /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Individual retweeting behavior on social networking sitesby Juan Shi, Kin Keung Lai, Gang Chen.
其他題名:	a study on individual information disseminating behavior on social networking sites /
作者:	Shi, Juan.
其他作者:	Lai, Kin Keung.
出版者:	Singapore :Springer Singapore :2020.
面頁冊數:	xvii, 132 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Online social networksPsychological aspects.
電子資源:	https://doi.org/10.1007/978-981-15-7376-7
ISBN:	9789811573767$q(electronic bk.)

Individual retweeting behavior on social networking sitesa study on individual information disseminating behavior on social networking sites /
Shi, Juan.

Individual retweeting behavior on social networking sitesa study on individual information disseminating behavior on social networking sites /[electronic resource] :by Juan Shi, Kin Keung Lai, Gang Chen. - Singapore :Springer Singapore :2020. - xvii, 132 p. :ill., digital ;24 cm.

1. 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.

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.

ISBN: 9789811573767$q(electronic bk.)

Standard No.: 10.1007/978-981-15-7376-7doiSubjects--Topical Terms:

606154
Online social networks
--Psychological aspects.

LC Class. No.: HM742

Dewey Class. No.: 302.30285

Individual retweeting behavior on social networking sitesa study on individual information disseminating behavior on social networking sites /
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505 0 $a 1. 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.
520 $a 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.
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