Social media has become a popular platform for millions of users to share activities and thoughts. Many applications are now tapping on social media to disseminate information (e.g., news), to promote products (e.g., advertisements), to manage customer relationship (e.g., customer feedback), and to source for investment (e.g., crowdfunding). Many of these applications require user profile knowledge to select the target social media users or to personalize messages to users. Social media user profiling is a task of constructing user profiles such as demographical labels, interests, and opinions, etc., using social media data. Among the social media user profiling research works, many focus on analyzing posted content. These works could run into the danger of non-representative findings as users often withhold some information when posting content on social media. This behavior is called selective self-disclosure. The challenge of profiling users with selective self-disclosure behavior motivates this dissertation, which consists of three pieces of research works.
Adoption dynamics, graphical models, brand factors, social network, diffusion, recommendation systems
PhD in Information Systems
Databases and Information Systems | Social Media
LIM, Ee Peng
School of Information Systems (SIS)
City or Country
Profiling social media users with selective self-disclosure behavior. (2016). Dissertations and Theses Collection.
Available at: http://ink.library.smu.edu.sg/etd_coll_all/1
Copyright Owner and License
Singapore Management University
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Available for download on Monday, May 21, 2018