Abstract
In recent years, users have increasingly focused on the privacy of social networking sites (SNS); users have reduced their self-disclosure intention. To attract users, SNS rely on active platforms that collect accurate user information, even though that information is supposed to be private. SNS marketers must understand the key elements for sustainable operation. This study aims to understand the influence of motivation (extrinsic and intrinsic) and self-disclosure on SNS through soft computing theories. First, based on a survey of 1108 users of SNS, this study used a dominance-based rough set approach to determine decision rules for self-disclosure intention on SNS. In addition, based on 11 social networking industry experts’ perspectives, this study validated the influence between the motivation attributes by using Decision-Making Trial and Evaluation Laboratory (DEMATEL). In this paper, the decision rules of users’ self-disclosure preference are presented, and the influences between motivation attributes are graphically depicted as a flow network graph. These findings can assist in addressing real-world decision problems, and can aid SNS marketers in anticipating, evaluating, and acting in accord with the self-disclosure motivations of SNS users. In this paper, practical and research implications are offered.
Highlights
Social networking sites (SNS) are popular multimedia communication channels that collect user profiles; registered members can use their profiles to share information or express opinions and attitudes [1]
To understand the influence of extrinsic and intrinsic motivation on the users’ self-disclosure intention on SNS, this study applied dominance-based rough set approach (DRSA) to infer decision rules from preference-ordered data, adopted decision-making trial and evaluation laboratory (DEMATEL) to examine the relationships between motivation attributes, and used a flow network graph to depict the results as a diagram
Motivation plays an important role in self-disclosure on SNS
Summary
Social networking sites (SNS) are popular multimedia communication channels that collect user profiles; registered members can use their profiles to share information or express opinions and attitudes [1]. The main concerns in application of a systemic decision model are as follows: (1) What motivation influences users’ self-disclosure intention on SNS? (3) What are the key extrinsic and intrinsic motivation attributes that influence users’ self-disclosure intention on SNS? To gain new insights regarding self-disclosure, this research presents a multiple criteria decision-making (MCDM) model by using soft computing theories to examine the key attributes of extrinsic and intrinsic motivation to understand how the predictors influence users’ self-disclosure on SNS. Through collection of user psychology data using a similar survey of a questionnaire, SNS marketers can better understand the attributes influencing self-disclosure. This study explains the extrinsic (wealth, fame, and image) and intrinsic motivations (self-esteem, personal growth, community feeling, self-directed pleasure, and relatedness) of self-disclosure on SNS by combining the DRSA, DEMATEL, and a flow network graph.
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