The New News

The Fast Pace of Tech­nology

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.

Psy­cho­graphic Mod­eling

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).

Dig­ital Ad­ver­tising

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.

Where Do We Get Our News?

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

Net­works and News

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").

Con­clu­sion

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.