Giving too much social support: social overload on social networking sites

Abstract

As the number of messages and social relationships embedded in social networking sites (SNS) increases, the amount of social information demanding a reaction from individuals increases as well. We observe that, as a consequence, SNS users feel they are giving too much social support to other SNS users. Drawing on social support theory (SST), we call this negative association with SNS usage ‘social overload’ and develop a latent variable to measure it. We then identify the theoretical antecedents and consequences of social overload and evaluate the social overload model empirically using interviews with 12 and a survey of 571 Facebook users. The results show that extent of usage, number of friends, subjective social support norms, and type of relationship (online-only vs offline friends) are factors that directly contribute to social overload while age has only an indirect effect. The psychological and behavioral consequences of social overload include feelings of SNS exhaustion by users, low levels of user satisfaction, and a high intention to reduce or even stop using SNS. The resulting theoretical implications for SST and SNS acceptance research are discussed and practical implications for organizations, SNS providers, and SNS users are drawn.

Keywords:

• IT continuance
• dark side of IT
• negative consequence of IT usage
• technostress
• satisfaction
• social media

An earlier version of this paper was presented at the European Conference on Information Systems (ECIS), Barcelona, in June 2012 (Maier et al, 2012c).

An earlier version of this paper was presented at the European Conference on Information Systems (ECIS), Barcelona, in June 2012 (Maier et al, 2012c).

Acknowledgements

This paper is dedicated to Ernst Maier, father of Christian Maier, who passed away on the day we submitted the revised version.

Notes

1 We scanned the Senior Scholars' Basket of Journals with its eight journals (MISQ, ISR, JMIS, JAIS, EJIS, ISJ, JSIS, and JIT) for the period 2002–2013 using stress-, social support-, and SNS-related search terms. For the identified articles, we performed forward and backward search as proposed by Webster and Watson (2002).

2 Techno-complexity would be the correct answer for this item.

3 χ²/df represents the minimum discrepancy divided by the degrees of freedom. GFI indicates the relative amount of variance and covariance that is explained by the model, whereas the AGFI adjusts GFI for the degrees of freedom. NFI and CFI indicate the percentage enhancement in fit over the baseline model. The RMSEA is a standardized estimation that is used to represent closeness of fit. SRMR represents the standardized difference between observed and predicted covariance. The IFI is used to address the issue of parsimony and sample size. The TLI adjusts NFI for the degrees of freedom and penalizes for model complexity.

Correction

This paper has been amended owing to the omission of information relating to the presentation of an earlier version.

Additional information

Notes on contributors

Christian Maier

About the Authors

Christian Maier is a doctoral fellow at the University of Bamberg. His research results about technostress, IT adoption and usage, user personality, and the IT workforce has been published in Journal of Strategic Information Systems, Journal of Business Economics, Business & Information Systems Engineering, and proceeding of various conferences including ICIS, ECIS, and AMCIS. He is the winner of the ACM SIGMIS Magid Igbaria Outstanding Conference Paper of the Year 2011 Award.

Sven Laumer

Sven Laumer is Assistant Professor at the University of Bamberg. His research results about IS adoption, user resistance, E-HRM, enterprise content management, social media, and the IT workworce has been published among others in Journal of Information Technology, Journal of Strategic Information Systems, MIS Quarterly Executive, Information Systems Frontiers, Journal of Business Economics, and Business & Information Systems Engineering. He is the winner of the ACM SIGMIS Magid Igbaria Outstanding Conference Paper of the Year 2011 Award and two best reviewer awards.

Andreas Eckhardt

Andreas Eckhardt is Researcher Associate at the Institute of Information Systems of Goethe University Frankfurt. His research on IS adoption, IS usage, HCI, technostress, E-HRM, and IT personnel turnover are published in two books, several conference proceedings, and journals including Journal of Information Technology, Journal of Strategic Information Systems, MIS Quarterly Executive, Information Systems Frontiers, Journal of Business Economics, and Business & Information Systems Engineering.

Tim Weitzel

Tim Weitzel is Professor and Chair of Information Systems and Services at the University of Bamberg, Germany. His research interests span IT management and usage, standardization, outsourcing, IT business alignment, and E-HRM. His research results are published in 14 books and in journals including MIS Quarterly, Journal of MIS, MIS Quarterly Executive, European Journal of IS, Journal of IT, Journal of SIS, Decision Support Systems, and Business and Information Systems Engineering and have been cited over 2.000 times.