My research comprises three broad areas in online/social media contexts, described below.
A list of my published research can be found on my Google Scholar page.
Online Self-Presentation
I study online self-presentation from the perspectives of message senders and audiences.
For message senders, I am interested in how people influence their own cognitions and emotions when they share things about themselves (e.g., past experiences, opinions on various issues) on social media. Additionally, what are the mechanisms that reinforce or undermine these self-effects?
Where audiences are concerned, I am interested in how people construe the extent to which another person’s online self-presentation (or even an organization’s assertions about itself) is authentic. Relatedly, how do audiences understand and interpret the need for message senders to perform authenticity in order to be perceived as genuinely authentic?
Showing that one is confident, successful, having a good time, or good looking has become the norm on social media. People appear to lead perfect lives. But can these near-perfect online self-presentations ironically lead to negative outcomes: perhaps feelings of inauthenticity for a message creator, or envy in an audience member?
This line of research has several aims. First, it seeks to rethink what it means to optimize one’s online self-presentations and avoid contributing to toxic positivity. Second, it strives to learn more about how media content that is thematically non-hedonic (such as those related to transience, melancholy, nature, art, gratitude, or bouncing back from failures) can be perceived as meaningful.
When people attempt to learn something (e.g., a scientific topic, more about another person), their own thoughts and feelings about the learning process may influence their subjective judgments concerning the learning outcome. For instance, a cognitively fluent learning process may engender greater (undue) confidence in one’s knowledge than a disfluent learning process. Even though these subjective judgments may occasionally be inaccurate, people nevertheless use them to determine how much time and effort they should put into learning.
My research in this domain explores how the way people think/feel about their web-based learning process (e.g., how they use generative AI or search engines) can influence their perceptions of their own knowledge or of their own intellectual abilities.