Last week I described some research issues I'd been working on here at the Amsterdam School of Communication Research (ASCoR) pertaining to online self-disclosure, impressions, and liking in computer-mediated communication. These issues prompted my visit here, to learn from Jochen Peter and Patti Valkenburg and their colleagues what insights and approaches we might compare or put together in order to untangle some issues in this research area. That work, as I mentioned, is moving forward with several new studies and some new ideas. But I also mentioned that I'd been probing my hosts on the matter of how and why they do things the way they do in their study of online communication. That has led to some fascinating ideas so far, and opened my eyes to new possibilities in my own work and some possible synthetic ideas.
Science pauses for the papparazzi |
In terms of how each of us does things—research that is—I
tend to do lab experiments, in which we ask a sixth of the participants to pursue
goal A (vs. B), while communicating via medium X (vs. Y or Z), to examine how
their communication changes and what effect it has on their attitudes and
feelings toward their partners. (The other 5/6ths of the participants are allocated to the alternative combinations.) Part of experimental processes involves being
able to rule out competing explanations (other than factors A/B and channels X/Y/Z)
for the outcomes we’re interested in. In contrast, although Jochen and Patti do
experiments, too, they primarily use survey techniques rather than lab
procedures: asking lots of people whether they are greater or lesser on
characteristic 1 and 2, whether they communicate with partner type i or ii, on
topics of greater or lesser intimacy, how much they use medium X or Y, with what naturally-occurring perceptions
they have about the qualities of these media, and how these things affect psychological
outcomes.
Why, I recently asked, do you deal with participants’ perceptions
of media, rather than use different media in different contexts and see what
they do? Sure, the perceptions should follow the situations and actions;
but if you just ask people about their perceptions and activities, how do you
know if they really know? What situation might they have been thinking about
when they answered the survey? Why deal with these interesting but elusive free-floating
characteristics?
Answer one, I learned, has to do with what lab experiments
often miss (or questionably assume), and answer 2 has to do with how those
missed characteristics can reverberate through the communication process.
Patti explained that one thing experiments can miss is that
some people, in reality, do not get exposed to every media situation. Some
people seek certain media and content, while others avoid it. (That’s answer
1.) The people who seek it may be different than those who do not, and, the way
they are different from others may also affect how they react to media messages
(and that’s the beginning of answer 2).
In experiments, everyone has an equal chance of being
exposed to Condition X, but in the world, a lot of people wouldn’t go near it.
And the lab reactions of people who we expose to Condition X, but who would not
normally go near Condition X, don’t tell us as much about the people who would
and do go near it.
These ideas are depicted and explained in Patti and Jochen’s
new article in the Journal of Communication, “The Differential
Susceptibility to Media Effects Model.”
It provides a really fascinating re-shuffling of the literature and how
we can think about how people deal with media differently than we mostly have
done.
Figure 1 from Valkenburg & Peter, 2013, p. 226 |
So I reflected somewhat cynically an idea that Mike Shapiro
pointed out a few years ago: From experimental lab research, I know a lot about
what would happen (if the average person had Goal A using Medium X), but
not much about what does happen.
Others know a great deal about what does
happen, but they can’t explain what causes it (using the most rigid definition
of causal explanation, by experimentally controlling participants’ exposure to
factors that provide rival explanations).
We’ve started discussing how to bridge these approaches.
We’ve begun identifying paradigm cases where researchers took “random”
variables – factors that are theoretically defined as perceptions or individual
differences which might vary normally but randomly among people – and rendered
them “active” (subject to controlled experimentation) for the sake of
theory-testing. In a situation such as that, if participants’ perceptions line
up with the specific experimental conditions we control, great; that’s a good
way to test a theory of perceptions and or through conditions.
What if perceptions do not line up with objective conditions? Now that
would be interesting, too. Maybe the perceptions that we theorized to be
important don’t actually mediate the processes we imagined they do. Or maybe
the conditions that we theorized to cause certain outcomes, actually stimulate
different perceptions, and there is some new intervening reaction that makes a
difference when people do A or B, in ways we did not contemplate. Or maybe we
have not been measuring perceptions, or implementing conditions, as well as we
thought we did. Or all of the above. Any of these conclusions suggest more work
to do to unwrap the mysteries of how people use media (in or out of
relationships) and how media affect them. We have more thinking and writing to do
on these ideas, but if we can synthesize a good framework it may enhance our
own research, and maybe influence the thinking and research by other students
like us.
Take the concept, anonymity. Sometimes researchers
conceive of it as not knowing who said what online. Others use it to refer to
not being seen visually online. In others’ research, it is the idea that people
cannot connect your online statements to your offline self. Could be any, could
be all, could be that most online communication is not very anonymous at all by
some definitions. Schouten, Valkenburg, and Peter argue that it is the perception
of the relevance of anonymity that might be most important. Which of these conceptions affects the relevance of anonymity? What about
contexts, such as fostering your SecondLife vs. answering your university
email -- don't these contexts differ in the relevance of anonymity? We could test which contexts and/or interfaces affect the perception of anonymity’s relevance, and
learn what differences in definitions really count, in terms of users’
perceptions and behavior.
There was another surprise. Just as I was reading about
Patti and Jochen’s new model, they were reading a model of interactive media my
colleagues and I suggested not long ago, too. It was largely influenced by our
study of new media and interpersonal goals, and Prof. Charles Atkin’s communicatory
utility theory in the 1970s. Chuck proposed that interpersonal goals lead
us to consume media in order to gather content to bring up and discuss in our
interpersonal conversations. We extended the argument by saying that different
interpersonal goals should affect the way we seek online (mediated)
information, what we selectively report to others that we found, what we
remember of it in this biased way, and that ultimately our own perceptions of
things may change by the goal-driven information-seeking we used media to do.
Patti was the first to discover the similarity among our positions:
Precursors to our media information-seeking (social, developmental, or
dispositional) affect in which media we seek information and how
we seek information from them, and these same factors affect how we process
(report, retain, recall) the information. Patti noted, “On p. 187 of your chapter you write: ‘We posit that the specific
interpersonal goals that prompt an individual's media consumption shape
attention to variations in the content and features of the topical information
one consumes, affecting its interpretation and recall.’”
They had a model of media effects. We had a model of
interpersonal interaction in a new media environment. These works have a lot in common. Our
task now is to see where these models mesh and where they diverge, and whether
the points of divergence can synthesize to expand the model’s reach and frame a
rather huge range of communication, in a logical and comprehensive
way.
Just as Prof. Peter Neijens and I had discussed in February, modern communication
is such that mass media researchers can’t ignore interpersonal dynamics; people
use media to tweet, chat, comment, and criticize messages that arrive via the mass media among each other, back and forth, in ways that affect the impact of mass media messages in serious
ways. Interpersonal communication researchers often need to consider media more,
since relationships initiate on dating sites, maintain themselves through
Facebook, and coordinate themselves through texting and email, etc. If media properties
affect the way relational messages play out (I think they do), they can't be
ignored. But they're complicated. As Laura Stafford wrote, “Media scholars and
relational scholars from many domains can inform each other. Insular inspection
only serves to constrain our understanding of the increasing complexities of
the ways relationships and media interact” (p. 96).
We’ll see what we can come
up with together in Amsterdam and beyond. Only you may not see too much more
about it until Reviewer B says okay.
(Can someone put references in blogs? Hope so because in this work you never get too far by yourself.)
- Atkin, C. K. (1973). Instrumental utilities and information seeking. In P. Clark (Ed.), New models for mass communication research (pp. 205-242). Beverly Hills, CA: Sage.
- Schouten, A. P., Valkenburg, P. M., & Peter, J. (2007). Precursors and underlying processes of adolescents’ online self-disclosure: Developing and testing an “Internet-attribute-perception” model. Media Psychology, 10, 292-315.
- Shapiro, M. A. (2002), Generalizability in communication research. Human Communication Research, 28, 491-500.
- Stafford, L. (2005). Maintaining long-distance and cross-residential relationships. Mahwah, NJ: Lawrence Erlbaum Associates.
- Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. Journal of Communication, 63, 221-243.
- Walther, J. B., Tong, S. T., DeAndrea, D. C., Carr, C., & Van Der Heide, B. (2011). A juxtaposition of social influences: Web 2.0 and the interaction of mass, interpersonal, and peer sources online. In Z. Birchmeier, B. Dietz-Uhler, & G. Stasser (Eds.), Strategic uses of social technology: An interactive perspective of social psychology (pp. 172-194). Cambridge, England: Cambridge University Press.