Social media anxiety, fatigue, and lurking behaviors are growing phenomena where users experience stress, exhaustion, and passive consumption on platforms.
Investigating motivations behind these behaviors is crucial for understanding user well-being, platform sustainability, and the evolving dynamics of online social interactions in our increasingly digital world.
Liu, X., Feng, R., Chen, X., & Yuan, Y. (2024). “Left on read” examining social media users’ lurking behavior: An integration of anxiety and social media fatigue. Frontiers in Psychology, 15, 1406895. https://doi.org/10.3389/fpsyg.2024.1406895
Key Points
- The study investigates factors influencing lurking behavior on social media platforms, focusing on WeChat users in China.
- Both intrinsic motivations (social comparison, privacy concerns) and extrinsic motivations (information overload, functional overload, social overload) positively affect users’ lurking behavior through social media fatigue and anxiety.
- Social media fatigue is positively associated with anxiety, and both factors contribute to increased lurking behavior.
- The research utilizes the Stressor-Strain-Outcome (SSO) model and Self-Determination Theory to examine the complex dynamics of social media user behavior.
- Findings suggest that social media platforms should address both intrinsic and extrinsic factors to mitigate user anxiety and fatigue, thereby fostering engagement and sustainable development.
- The study highlights the importance of understanding lurking behavior for the advancement of social media platforms and user experience optimization.
Rationale
The widespread use of social media has transformed user behavior, leading to an increase in lurking users who passively consume content without actively engaging.
This phenomenon can impede the sustainable development of social media platforms (Barnidge et al., 2023).
Previous research has attributed lurking behavior to factors such as computer anxiety (Osatuyi, 2015), technology overload (Karr-Wisniewski & Lu, 2010), and information security awareness (Ortiz et al., 2018).
However, most studies have focused on individual factors, neglecting the broader psychological motivations and comprehensive impact of the external environment on lurking behavior.
This study aims to address this gap by investigating the impact of both intrinsic and extrinsic motivational factors on social media users’ anxiety, fatigue, and lurking behavior.
By adopting the SSO model and drawing upon Self-Determination Theory (Deci et al., 1991; Hung et al., 2011), the research seeks to uncover the underlying motivations driving social media users’ lurking behavior and shed light on the essence of “left on read” behavior.
The study’s findings can contribute to optimizing social media platform functionality and offer enhanced solutions to mitigate issues related to users’ lurking behavior.
Method
The study employed a structural equation model based on the SSO theoretical framework to test and validate the proposed hypotheses.
Data was collected through online surveys and analyzed using SPSS 27.0 and AMOS 24.0 software.
Procedure
Participants completed a two-part questionnaire. The first part gathered demographic information, while the second part included measures for all constructs outlined in the research model.
The questionnaire underwent rigorous validation, including back-translation and pre-testing procedures.
Sample
The study collected data from 836 valid online surveys of WeChat users in China. The sample consisted of 388 males (46.4%) and 448 females (53.6%).
The majority of participants were aged 21-40 (70.5%), with high frequency and duration of WeChat usage.
Measures
- Social comparison (adapted from Nisar et al., 2019; Jabeen et al., 2023)
- Privacy concerns (adapted from Cain & Imre, 2022)
- Information overload (adapted from Zhang et al., 2016; Guo et al., 2020)
- Functional overload (adapted from Guo et al., 2020; Lee et al., 2016)
- Social overload (adapted from Guo et al., 2020; Fu et al., 2020)
- Anxiety (adapted from Liu et al., 2020)
- Social media fatigue (adapted from Jabeen et al., 2023; Kaur et al., 2021)
- Lurking behavior (adapted from Zhang et al., 2021; Hong et al., 2023)
All items were assessed using a 5-point Likert scale.
Statistical measures
The study used structural equation modeling (SEM) to analyze the relationships between latent variables.
Model fit was assessed using chi-square degrees of freedom ratio, GFI, CFI, NFI, IFI, TLI, and RMSEA. The percentile Bootstrap method was employed for mediation effect analysis.
Results
- Social comparison positively affects anxiety (β = 0.190) and social media fatigue (β = 0.137)
- Privacy concerns positively affect anxiety (β = 0.209) and social media fatigue (β = 0.207)
- Functional overload positively affects anxiety (β = 0.221) and social media fatigue (β = 0.187)
- Information overload positively affects anxiety (β = 0.228) and social media fatigue (β = 0.097)
- Social overload positively affects anxiety (β = 0.214) and social media fatigue (β = 0.301)
- Anxiety positively affects lurking behavior (β = 0.126)
- Social media fatigue positively affects lurking behavior (β = 0.291) and anxiety (β = 0.139)
- All relationships were statistically significant (p < 0.01)
Insight
The study reveals that both intrinsic and extrinsic factors contribute to social media users’ lurking behavior through the mediating effects of anxiety and social media fatigue.
Social comparison and privacy concerns, as intrinsic motivations, significantly impact users’ psychological states, leading to increased anxiety and fatigue.
This suggests that users’ self-perceptions and concerns about data protection play crucial roles in shaping their engagement with social media platforms.
Extrinsic factors, including functional overload, information overload, and social overload, also contribute to anxiety and fatigue.
This indicates that the abundance of features, information, and social demands on social media platforms can overwhelm users, leading to negative psychological states and reduced engagement.
The study extends previous research by integrating both intrinsic and extrinsic factors and examining their combined effects on lurking behavior.
It provides a more comprehensive understanding of the complex dynamics underlying social media user behavior, moving beyond single-factor explanations.
Future research could explore the potential positive aspects of lurking behavior and investigate how these findings apply to different social media platforms and cultural contexts.
Additionally, examining the long-term effects of lurking behavior on user satisfaction and platform sustainability could provide valuable insights for social media developers and marketers.
Implications
The findings have significant implications for social media platform design and user experience optimization.
Platform developers should focus on addressing both intrinsic and extrinsic factors to reduce user anxiety and fatigue.
This may involve implementing more robust privacy protection measures, providing users with greater control over their social comparisons, and refining content filtering algorithms to reduce information overload.
For clinical practice, the study highlights the importance of considering social media use patterns when addressing anxiety and fatigue in clients.
Mental health professionals should be aware of the potential negative impacts of excessive social media use and the role of lurking behavior in psychological well-being.
Future research could explore interventions aimed at reducing social media fatigue and anxiety, such as mindfulness-based approaches or digital well-being tools.
Additionally, longitudinal studies could investigate the long-term effects of lurking behavior on social relationships and overall life satisfaction.
Strengths
This study had several methodological strengths, including:
- Large sample size (N = 836) providing robust statistical power
- Comprehensive theoretical framework integrating SSO model and Self-Determination Theory
- Examination of both intrinsic and extrinsic factors influencing lurking behavior
- Use of structural equation modeling for complex analysis of relationships between variables
- Rigorous validation process for the questionnaire, including back-translation and pre-testing
Limitations
The study also had several limitations, including:
- The sample primarily represents middle-aged and young individuals, with less representation from older age groups.
- The research is limited to China and WeChat users, potentially limiting generalizability to other cultural contexts and social media platforms.
- The cross-sectional nature of the study prevents conclusions about causality or long-term effects of lurking behavior.
- The study focuses primarily on negative aspects of lurking behavior, potentially overlooking potential positive aspects or rational motivations for such behavior.
These limitations suggest the need for future research to include more diverse age groups, expand to different cultural contexts and social media platforms, and employ longitudinal designs to better understand the causal relationships and long-term effects of lurking behavior.
References
Primary reference
Liu, X., Feng, R., Chen, X., & Yuan, Y. (2024). “Left on read” examining social media users’ lurking behavior: An integration of anxiety and social media fatigue. Frontiers in Psychology, 15, 1406895. https://doi.org/10.3389/fpsyg.2024.1406895
Other references
Barnidge, M., Peacock, C., Kim, B., Kim, Y., & Xenos, M. A. (2022). Networks and Selective Avoidance: How Social Media Networks Influence Unfriending and Other Avoidance Behaviors. Social Science Computer Review. https://doi.org/10.1177_08944393211069628
Cain, J. A., & Imre, I. (2021). Everybody wants some: Collection and control of personal information, privacy concerns, and social media use. New Media & Society. https://doi.org/10.1177/14614448211000327
Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and Education: The Self-Determination Perspective. Educational Psychologist, 26(3–4), 325–346. https://doi.org/10.1080/00461520.1991.9653137
Fu, S., Li, H., Liu, Y., Pirkkalainen, H., & Salo, M. (2020). Social media overload, exhaustion, and use discontinuance: Examining the effects of information overload, system feature overload, and social overload. Information Processing & Management, 57(6), 102307. https://doi.org/10.1016/j.ipm.2020.102307
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Keep Learning
Socratic questions for a college class to discuss this paper:
- How might cultural differences impact the factors influencing lurking behavior on social media platforms?
- What potential positive aspects of lurking behavior could be explored in future research?
- How can social media platforms balance the need for user engagement with the potential negative effects of overload and fatigue?
- In what ways might the findings of this study apply to professional networking platforms like LinkedIn?
- How could the concept of “digital well-being” be incorporated into social media platform design based on these findings?
- What ethical considerations should be taken into account when developing strategies to reduce lurking behavior?
- How might the COVID-19 pandemic have influenced social media usage patterns and lurking behavior?
- In what ways could the findings of this study inform digital literacy education programs?
- How might the factors influencing lurking behavior differ across various age groups?
- What potential long-term societal impacts could widespread lurking behavior have on social interaction and communication patterns?
