An empirical study of the factors affecting social network service use

By O. Kwon, Yixing Wen. Computers in Human Behavior, 2010

738 citations recorded by the source corpus.

Subfields: Communication, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/bfee70ca974dc3939ca7d6cb4349bdf51aa80dcf

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Citations in the corpus

Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of #Depression (2017, background): “In the context of SNSs, social support can be a motivator for use [43,67] as well as an outcome [33].”
The role of perceived social capital and flow experience in building users' continuance intention to social networking sites in China (2012, neutral): “Although previous studies have proven that perceived usefulness construct has significant impact on users’ intention to use SNSs (Kim, 2011; Kwon & Wen, 2010; Lin & Lu, 2011), it is not known how different aspects of perceived usefulness influence users’ satisfaction and continuance intention (Yin…”
Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity (2016, neutral): “However, these studies have focused on either SNS use (Kwon & Wen, 2010; Pelling & White, 2009; Sledgianowski & Kulviwat, 2008) or continued SNS use (Choi, 2013) with little attention paid to user behavior concerning SNS ads.”
Why people use social networking sites: An empirical study integrating network externalities and motivation theory (2011, background): “Many scholars (Lee, 2009; Lu, Table 1 Previous research on network externalities.”
Customers' need for uniqueness theory versus brand congruence theory: The impact on satisfaction with social network sites (2020, positive): “If members perceive an SNS as being useful then they are more likely to be satisfied with the social network and be more engaged (Kang and Lee, 2010; Kwon and Wen, 2010; Lin and Lu, 2011; Sledgianowski and Kulviwat, 2009).”
Millennials, narcissism, and social networking: What narcissists do on social networking sites and why (2011, background): “This increase in narcissism has occurred alongside the increased usage of social networking sites (SNSs) such as MySpace and Facebook, which have now amassed over 100 million users among them (Kwon & Wen, 2010).”
Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning (2013, result): “This is consistent with previous research on social networking systems, which support the fact that perceived ease of use more important than perceived usefulness for technology adoption in a Web 2.0 environment (Kwon & Wen, 2010).”
What drives successful social networking services? A comparative analysis of user acceptance of Facebook and Twitter (2014, background): “More speciﬁcally, TAM has been particularly useful in investigating the adoption of Internet-based social media technologies (Kwon & Wen, 2010; Rauniar, Rawski, Yang, & Johnson, 2014; Shin, 2010; Shin & Shin, 2011).”
Expanding the Technology Acceptance Model with the Inclusion of Trust, Social Influence, and Health Valuation to Determine the Predictors of German Users’ Willingness to Continue using a Fitness App: A Structural Equation Modeling Approach (2018, background): “…the impact of the two constructs on the adoption of various forms of technology (e.g. Carter & Belanger, 2005; Chau & Lai, 2003; Gefen et al., 2003; Kwon & Wen, 2010; Wu & Wang, 2005) and, specifically, on people ’ s inclination to continue using health apps (Cho, 2016; Cho et al., 2015) While…”
“Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model (2023, background): “Social influence plays a vital role in early technology adoption (Venkatesh et al., 2003; [109,110].”
Online Social Networking and Addiction—A Review of the Psychological Literature (2011, neutral): “network [35].”