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On Assuming vs. Anticipating, or Why Uses and Gratifications Theory is Still No. 1

For established media effects frameworks to continue to work well, scholars need to move from assuming to anticipating. To illustrate this, let’s examine three, existing theoretical frameworks and their various assumptions, especially in new media contexts. From here we may better understand what researchers should anticipate in order for these frameworks to continue to produce valuable findings.

The hypodermic effects model is a full-effects framework that posits a reductionist sender/receiver model. In it, the “all-powerful” media sends it messages to the audience, “injecting” its (insidious) messaging into their (passive) brains. While this model was popular from the 1920s on through the 1950s, it assumes way too much. For example, the model assumes that effects are one-way and one-time. It also assumes that the sender is a seemingly dominant force that holds power over an assumed passive audience (Park and Pooley, 2008). As we know, there are simply too many variables in today’s fragmented media landscape that easily discount this model that, at once, “inoculates” audiences. Moreover, the hegemonic media of yore doesn’t really exist in today’s rich (but fragmented) new media environment.

The two-step flow model is a limited effects framework that posits messaging flows through a kind of intermediary that vets its content for audiences. In it, media messages flow through opinion leaders before reaching audiences, which, in the model, are labeled “opinion followers.” This model also assumes much. For example, it assumes that people who are less informed follow more informed opinion leaders, to essentially create and/or shape their opinions. It also assumes opinion leaders are persuasive and can cause people to act, such as causing people to turn out to vote (Park and Pooley, 2008). The model is still very relevant in new media contexts because it at least distinguishes stages of mediated communication, anticipating for variability.  For example, bloggers (opinion leaders) vet information/media messages by a) acting as a gatekeeper and b) interpreting the information to fit the expectations of their audiences (opinion followers). The model certainly takes into consideration an intermediary, the opinion leader, but doesn’t take into account bi-directionality of messaging.

The uses and gratifications framework posits that audiences use media to fulfill certain gratifications. The model assumes that the audience is active and that media use is goal-oriented. In the context of research, the model also assumes that what is at play are social and psychological origins of needs. It also doesn’t take into account the social context of media use (Katz, Blumler and Gurevitch, 1973). However, of the three models in this piece, uses and gratifications simultaneously assumes the least. This may account for why its use is still so widespread in media effects research today.

What these three frameworks demonstrate is the need for researchers to move from assuming to anticipating. As the drawing above illustrates, by including anticipations into the uses and gratifications model itself, the model becomes more relevant, versatile and, perhaps, timeless because it removes assumptions that can damage credibility, relativity and efficacy. In order for existing frameworks to maintain relevance and efficacy (i.e. hypodermic effects and two-step flow models), researchers should anticipate external factors and variables to the point where they are built-in to the frameworks themselves (as the model above illustrates). For example, rather than simply assume what might affect a subject’s media use, one should anticipate factors that will influence a subject’s media use so data, results and conclusions bear greater depth. A teenager doesn’t simply tweet while he’s watching a television show; he tweets while watching a television show that he has followed serially for three years because he is connecting with fans like him who emotionally identify with the main character for similar reasons. Anticipating such media use factors, rather than assuming he’s just a teen who multitasks different media because he is a member of Generation Y, is what models of the future need to imbue.

As Farnsworth and Owen (2004) state in their study on Internet use and the 2000 presidential election, “it makes a great deal of sense for researchers to recognize the active dimension of individuals’ media consumption that uses and gratifications approaches take into account.” In their study, they explicitly articulate anticipating information-seeking as a possible effect of their subjects, basing their hypotheses on this anticipation—perhaps alluding to how versatile uses and gratifications continues to be for scholars, and how anticipating made their study all the more tenable.

At the most basic denotative level, the difference between assuming versus anticipating lies in the basis for forming and incorporating said elements into research. Defined, to assume is “to suppose to be the case, without proof” (Apple dictionary). Defined, to anticipate is “to regard as probable; expect or predict” (Apple dictionary).  In my view, “probable” beats “without proof.”

Apple dictionary: assume. Retrieved from personal computer application.

Apple dictionary: anticipate. Retrieved from personal computer application.

Farnsworth, Stephen J. and Diana Owen, “Internet Use and the 2000 Presidential Election,” Electoral Studies, Sep 2004, Vol. 23 Issue 3, p. 415-429.

Katz E., Jay G. Blumler, and Michael Gurevitch, “Uses and Gratifications Research,” Public Opinion Quarterly, Winter 1973-74, Vol. 37 Issue 4, p. 509.

Park, David W., and Jefferson Pooley (eds.). The History of Media and Communication Research: Contested Memories. New York: Peter Lang, 2008.

Semi-ironic drawing created by Andy Lewandowski.

* For the purpose of creating an analogous term to “assumptions,” the word “anticipations” was created.

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About Andrew D. Lewandowski

Andrew Lewandowski is a Georgetown University graduate student in the Communication, Culture & Technology program.

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