Publication | Closed Access
Understanding Internet Usage
514
Citations
77
References
2001
Year
Internet Traffic AnalysisInternet ScienceSocial PsychologySocial ValueSocial InfluenceCommunicationInternet BehaviorPsychologySocial SciencesSocial MediaMedia EffectsCyberpsychologyInternet ModelingStructural Equation ModelingMedia PsychologyProblematic Social Medium UseMedia InfluenceInternet StudiesTechnologySocial ComputingTechnological AddictionInternet Addiction DisorderArtsInternet UsageInternet Addiction
Prior uses‑and‑gratifications studies have applied the framework to Internet use, yet they explain little variance and yield conflicting results. This research identifies new variables from social‑cognitive theory to better explain Internet usage and resolve inconsistencies. The study developed self‑efficacy and self‑disparagement measures for Internet behavior, interpreted addiction as deficient self‑regulation, and examined negative online outcomes' impact on usage. In a survey of 171 college students, the social‑cognitive model explained 60% of variance in Internet usage, markedly improving on previous approaches.
Several studies have applied uses and gratifications to explain Internet usage. Like Bandura’s social-cognitive theory, the uses and gratifications framework explains media use in terms of expected positive outcomes, or gratifications. However, previous uses and gratifications research accounted for little variance in Internet behavior, although there were conflicting results. This research identifies new variables from social-cognitive theory that might further explain Internet usage and resolve inconsistencies in prior research. Measures of self-efficacy and self-disparagement were developed for the domain of Internet behavior. Internet addiction was interpreted as a deficient self-regulation within the social-cognitive framework. Finally, the negative outcomes of online behavior were analyzed for their impact on Internet usage. In a survey of 171 college students, the social-cognitive model explained 60% of the available variance in Internet usage using multiple regression analysis, a significant improvement over prior uses and gratifications research.
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