7:40pm | 4/11/2018
Last year I wrote a first draft of a paper, The Internet of Anxiety, which essentially documented the growing pains of the universe of information and communication technologies (ICTs) from radio to the Internet.1 The present media ecosystem seems to be the result of a "coming of age" of the past 30 years of technological innovation. Though it can hardly be said to be a moment of rest, there is a sense that we are experiencing fewer paradigm-shifting changes in technology.
Facebook's infamous call to "move fast and break things" seems to have reached a point where everything is so broken that everyone's being forced to pick up the pieces, and take a retrospective look at how and when everything got so screwed up. It's an understatement to say the Internet has changed the way we live. In the last post, I talked a bit about the way in which the rise of digital advertising has devastated printed news— and what measures are being taken to revitalize those traditional news outlets which have managed to survive.
As detailed in The Internet of Anxiety, the business model of digital ad-based revenue has done more than harm print media. Today, with the advent of programmatic advertising, this market has catalyzed the already prolific spread of misinformation and "fake news" by fragmenting the relationship between the ad buyer, advertiser and publisher. Ads have been "programmed" to gain impressions not only within specific cultural or social spaces online, but to follow a particular psychographic model (an audience).
Firstly, this segmentation is utterly destructive to accountability and opens the doors for fraud on a massive scale. Secondly, it allows advertisers to track users' data— especially in the United States where digital privacy is relatively unprotected. It's also my understanding that this undermines the value of these audiences to the sites on which the ads have been displayed— with advertisers retaining user data and gains impressions across other sites.
The current monetization strategy that's being adopted in lieu of— or supplementing— ad-based revenue models is a metered paywall, or subscription-based revenue. It might be that the paid model simply could not have existed at any other time. In the "wild west" of the early Web, services like LimeWire and Napster— though relatively short-lived— were wholly embraced as epitomizing an open and free Internet. Even Google had a part in this illicit digital economy when it made the decision to down-rank search results that led to paywalled content.
RSS and now Facebook's "feed" have also done wonders to reduce the value of knowledge journalists and bloggers add to information. Only recently have major news operations like The New York Times been able to stabilize their revenue on a subscription-based model, and others are doing the same (largely out of necessity)— adding credence to the concept that there is value in well-interpreted and curated information streams.
However, this also introduces further complexity into the equation of information equality, begging the question: Should the right to quality news reflect income? Perhaps we will see special pricing, or subsidized subscriptions; but for now it remains to be seen.
The function of news, historically, has always been to maintain an informed public. In News in a Time of Factual Recession: Understanding Networked Media and Populist Knowledge (soon to be published), John Wihbey asks:
How does a democracy operate without commonly agreed-upon bodies of fact? Who is responsible for provisioning those facts? How can media institutions best serve democracy?2
Anyone would be hard-pressed to come up with an answer to these questions, but Wihbey lends some incredible insight in his book. Drawing upon the fairly infantile network sciences, Wihbey remarks on a number of critical studies on the structure of today's ICT channels. In the past few decades, commonalities in a network's "typology"— or the weight of a set of nodes and how they connect— have revealed a set of near-universal principles in how they behave, indiscriminately of function.
Through an understanding of the character of these networks journalists have been able to formulate a deeper understanding of how information flows between people, communities, and digital platforms online. The value that emerges from this understanding is the ability to effectively "crowdsource" knowledge; direct information for increased engagement; discern patterns in large datasets; and increase the connectivity of disparate communities.
Among the many players in network science, Wihbey singles out several key studies and findings:
Stanley Milgram's Six Degrees of Separation3
Recall the popular "six degrees of Kevin Bacon" game: someone names an actor or actress and the player has to connect them back to Kevin Bacon through 6 or fewer movies.
Albert-László Barabási's definition of the scale-free network4
The "rich get richer" phenomenon: Coined by Barabási, scale-free networks follow a power law distribution in which a very small percentage of nodes have an incredible amount of connections while a similarly incredible amount have very few (if any) connections.
Duncan Watts and Steven Strogatz' Collective Dynamics of Small-World Networks5
An affirmation of both Milgrim's six degrees of separation (1967) and The Strength of Weak Ties by Mark Granovetter (1973), this study showed that while strong ties are important for developing knowledge internally, it is often "weak ties"— acquaintances rather than deep friendships— that reveal and convey outstanding or atypical information to those developed communities.6 Additionally, nodes in a network will tend to gravitate toward more highly-connected and longer-established hubs (known as "preferential attachment").
From my experience in César Hidalgo's class, Networks, Complexity and Its Applications, I can say that the research Wihbey selects for his book is foundational to an understanding of network science— especially in relation to the transfer of knowledge through the Web. Undoubtedly, the insights gleaned from an interdisciplinary mix of modern social science with the analytic skills of journalism will produce some remarkable transformations in how news is created, curated, and disseminated.
I would definitely recommend looking for the final version of Wihbey's book when it comes out. I think it couldn't be more relevant to how we understand media today.
N O T E S
1 Tompkins, Daniel W. "The Internet of Anxiety: Media Freedom, Technopolitics, and How Communist Cuba Could Save American Democracy." Research paper, Harvard University, 2017.
2 Wihbey, John P. News in a Time of Factual Recession: Understanding Networked Media and Populist Knowledge. Manuscript, MIT Press, 2018.
3 Milgram, Stanley. "The Small World Problem". Psychology Today. Ziff-Davis Publishing Company, 1967.
4 Barabási, A. "Emergence of Scaling in Random Networks." Science 286, no. 5439 (1999): 509-12. doi: 10.1126/science.286.5439.509.
5 Watts, Duncan J., and Steven H. Strogatz. "Collective Dynamics of ‘small-world’ Networks." Nature 393, no. 6684 (1998): 440-42. doi:10.1038/30918.
6 Granovetter, Mark S. "The Strength of Weak Ties." American Journal of Sociology 78, no. 6 (1973): 1360-380. doi:10.1086/225469.