Advancing Knowledge Gap theory in the Social Media Context: The Mediated Knowledge Acquisition Model (MKAM) and its Pilot Study


Social media platforms are evolving into important sources of information that complement their traditional counterparts. Researchers (e.g. Khoo, 2014) also claim it is an important platform for news sharing, and is unique in its users’ ability to generate content. Extant literature investigating knowledge acquisition in social media found that knowledge gained via social media is dependent on different factors, this implies that a knowledge gap in social media exists, but here the independent variable Tichenor, Donohue and Olien (1970) employs, socioeconomic status, is too general and quite exclusionary. This paper addresses this issue and incorporates personal susceptibilities into the Mediated Knowledge Acquisition Model (MKAM) which depicts the process of knowledge acquisition in social media.

The MKAM integrates existing findings and puts forward four propositions based on Valkenburg and Peter’s (2013) Differential Susceptibility to Media Effects Model.

Firstly, the three differential susceptibility variables, namely Need for Cognition (NfC, as the “motivation”; Cacioppo et al., 1984), New Media Literacy (NML, as the “skill”; Lee, Chen, Li, & Lin, 2015), and Curated Flow in Social Media (as a mix of personal interest, social issues, and media’s algorithmic properties; Thorson & Wells, 2016), affect Informational Social Media Use (ISU). These variables take both individual differences and differing social media environments into consideration.

Secondly, Cacioppo and Petty’s (1984) elaboration likelihood model is used to define two possible cognitive response states (central or peripheral processing) which mediates the effect of ISU on knowledge acquisition.

Proposition three states that the differential susceptibility variables mentioned in proposition 1 also moderate the effect of informational social media use on knowledge acquisition.

The fourth proposition states that knowledge acquisition has a transactional effect on the differential susceptibility variables, ISU, and elaboration likelihood. This proposition explains why the knowledge acquisition gap is widening. People who have stronger abilities to acquire knowledge will benefit from their stored knowledge. Which illustrates that those that can acquire more information, will acquire more information, and will continue to acquire more information.

Lastly, to examine whether the model is testable, we conducted a pilot study, combining survey, interviews and content analyses. Results show a Cronbach’s alpha of .81 for NfC, and of .79 for NML scale. ISU and acquired knowledge were tested in a structured interview with a Twitter-browsing exercise, the screen recording of which was content analyzed along with the audio clips of the interview. Results show that these methods are good measures. The patterns observed in the data indicate that the relationships between NFC and ISU, and as well ISU and acquired knowledge may exist, meaning these hypotheses have the potential to be observed in reality.

The MKAM advances the knowledge gap hypothesis to include social media, where people of all socioeconomic status conglomerate and in a time where acquiring knowledge is no longer incumbent upon class but on personal differences through its opportunistic information acquisition feed feature. This model also implies that to harness social media’s power as an information source, social media literacy education is needed.