The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.2307/3151312 · Cited by 109,314
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
(1984) · Cited by 81,983
The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148
Case Study Research: Design and Methods
Chaiklin, H. (1991) · The Journal of Nervous and Mental Disease · doi:10.1097/00005053-199102000-00025 · Cited by 39,535
Herne, H., Cooley, W. W., & Lohnes, P. R. (1973) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344428 · Cited by 35,697
Significance tests and goodness of fit in the analysis of covariance structures.
Bentler, P. M., & Bonett, D. G. (1980) · Psychological Bulletin · doi:10.1037//0033-2909.88.3.588 · Cited by 19,023
Cited by
Tarafdar, M., Cooper, C. L., & Stich, J. (2019) · Information Systems Journal · doi:10.1111/isj.12169 · Cited by 1,085
Fu, S., Li, H., Liu, Y., Pirkkalainen, H., & Salo, M. (2020) · Information Processing & Management · doi:10.1016/j.ipm.2020.102307 · Cited by 462
Research on information systems failures and successes: Status update and future directions
Dwivedi, Y. K., Wastell, D., Laumer, S., Henriksen, H. Z., Myers, M. D., Bunker, D., Elbanna, A., Ravishankar, M. N., & Srivastava, S. C. (2015) · Information Systems Frontiers · doi:10.1007/s10796-014-9500-y · Cited by 448
Self-citationEmpirical investigation of Facebook discontinues usage intentions based on SOR paradigm
Luqman, A., Cao, X., Ali, A., Masood, A., & Yu, L. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.01.020 · Cited by 425
Definition, symptoms and risk of techno-stress: a systematic review
La Torre, G., Esposito, A., Sciarra, I., & Chiappetta, M. (2019) · International Archives of Occupational and Environmental Health · doi:10.1007/s00420-018-1352-1 · Cited by 409
Metadata
- Authors
- Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T.
- Venue
- European Journal of Information Systems
- Publisher
- Informa UK Limited
- Published
- 2015-09
- Volume
- 24
- Issue
- 5
- Pages
- 447-464
- ISSN
- 0960-085X (ISSN-L)
- 1476-9344
- OpenAlex
- W2058084111
- Cited by
- 639
- References
- 111
- FWCI
- 90.80
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Giving too much social support: social overload on social networking sites. https://app.cochat.ai/papers/10.1057/ejis.2014.3
- The paper
- Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2015). Giving too much social support: social overload on social networking sites. European Journal of Information Systems. https://doi.org/10.1057/ejis.2014.3
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
