Content creators as social influencers: predicting online video posting behaviors

Abstract Purpose Creative content influencers are increasingly seizing the opportunity not only to express themselves, but also to monetize their videos and become entrepreneurs. The present study tests an integrative framework to determine whether the “creative influencers environment” impacts the degree of motivation for posting videos online, alongside the gratifications derived from such activity. Design/methodology/approach Utilizing a national online survey of video “creators” ( n = 327), we test a hierarchical model assessing the impact of social categories, personality factors (e.g., narcissism), and mediated communication constructs (e.g., uses and gratifications [U&G]). Findings Multiple regression analyses explain roughly half or more of the variance in our models for predicting (1) motivations for and (2) gratifications received from posting videos on social media. Practical implications Study findings reveal a different mix of predictors for each video content category that creative influencers post on social media. This includes a strong pattern of influences on posting motivations from the larger environment in which people live, social categories, and personality factors, but not from the use of legacy media nor the use of newer technologies. Social implications Results also underscore “different influences for different types of content,” which can be explained by a “content trumps form” theme that has emerged in recent research. Overall, mixed support was found for the proposed model, although we did establish this collection of constructs as important in predicting the strength of gratifications received and motivations sought by posting videos on social media. Originality/value The present analysis of larger environment factors, social categories, personality indicators, and use of media (legacy and newer) helps profile a social media “creator culture” for the production of online videos. Study findings offer a clear signpost that an additional component could be added here—that of “content types” for online videos—as a moderator for the variegated predictive power of the model components.