Making sense from the noise

As the tech­nol­ogy to pub­lish on the web becomes more stream­lined and the process from brain­storm to pub­li­ca­tion short­ens the abil­ity to aggre­gate and fil­ter will be immensely impor­tant. In order to make sense out of all this infor­ma­tion pub­lished and dis­trib­uted in real-time online we need a solid set of tools to fil­ter the impor­tant infor­ma­tion from the noise.

In a world with widely avail­able online pub­lish­ing tools we need ways of see­ing rela­tion­ships between data. From a polit­i­cal stand­point the abil­ity to fil­ter for rel­e­vant data and rela­tion­ships is invalu­able. We finally have tools devel­oped enough to allow us to aggre­gate and fil­ter infor­ma­tion to find these impor­tant rela­tion­ships. More impor­tantly, the tools that we now pos­sess are in the con­trol of indi­vid­u­als who can now aggre­gate and fil­ter their own per­son­al­ized infor­ma­tion flows. Among the many data aggre­ga­tion tools out there two are par­tic­u­larly use­ful in their appli­ca­tion to polit­i­cal par­tic­i­pa­tion: Google Reader and Fever.

The mod­ern tools that have devel­oped around aggre­gat­ing and fil­ter­ing data are tremen­dously flex­i­ble and pow­er­ful. These tech­nolo­gies empower more refined aggre­ga­tion that allows for a more informed pub­lic. Information is the key to well formed polit­i­cal deci­sions and tools like Google Reader and Fever give the American pub­lic the oppor­tu­nity to par­take in more informed polit­i­cal participation.

The tech­nol­ogy of aggregation

The main­stay of aggre­gat­ing data online has, since its inven­tion in the late 1990s, been Really Simple Syndication. This tech­nol­ogy, com­monly known as RSS, allows for users to auto­mate the sub­scrip­tion process to streams of infor­ma­tion online.1 Any site that pro­vides an RSS feed of con­tent can be sub­scribed to by a user using an RSS client like Google Reader or Fever. After sub­scrib­ing all con­tent feeds auto­mat­i­cally update after publication.

This tech­nol­ogy is already a default stan­dard on news sites, blog­ging plat­forms, pho­tog­ra­phy sites, and social appli­ca­tions like Twitter. Furthermore, it is an open tech­nol­ogy that can be imple­mented free of charge which means there are more client appli­ca­tions than could be cov­ered. Due to this mas­sive num­ber of client appli­ca­tions this essay will focus upon the two pieces of soft­ware that hold the great­est appli­ca­tion to polit­i­cal par­tic­i­pa­tion in the United States: Google Reader and Fever.

Fever, an RSS reader designed and devel­oped by Shaun Inman, was released in the sum­mer of 2009, It took a dif­fer­ent approach to read­ing infor­ma­tion through RSS. While the pre­vi­ous par­a­digm of RSS sub­scrip­tions had been to treat them like an email inbox, Fever approaches the model from a dif­fer­ent stand­point. Instead of dis­play­ing a list of unread items, sim­i­lar to an inbox, that only dis­ap­pear when all are read Fever allows for users to focus on just what is impor­tant to them while not feel­ing like they will miss other impor­tant news.

By mov­ing past the inbox mind­set of RSS read­ing, Fever changes the way users dis­cover and read feeds on the web. Instead of hav­ing to make a choice between sub­scrib­ing to a plethora of feeds (thus over­whelm­ing them­selves) or sub­scrib­ing to a select few feeds (poten­tially miss­ing impor­tant news), Fever approaches the prob­lem by encour­ag­ing users to make a dis­tinc­tion between essen­tial and sup­ple­men­tary infor­ma­tion sources while still sub­scrib­ing to both. Essential feeds are marked as “Kindling” while sup­ple­men­tary feeds are put into a “Sparks” folder.

These two des­ig­na­tions of con­tent are, together, the source of Fever’s most polit­i­cally impor­tant aspect: the Hot List. Shaun Inman describes the Hot List on Fever’s site by say­ing that,

Fever reads your feeds and picks out the most fre­quently talked about links from a cus­tomiz­able time period. Unlike tra­di­tional aggre­ga­tors, Fever works bet­ter the more feeds you follow.

Fever ana­lyzes the links of sources in both the Kindling and Sparks fold­ers. Through this analy­sis it then presents the most pop­u­lar sto­ries as deter­mined by the sources one fol­lows. This Hot List can be nar­rowed down to a range of days or for the most recent week. Furthermore, not only does it show the most linked to items but it also shows the orig­i­nat­ing sources for those items. Thus, it allows a user to see the most pop­u­lar items and how they relate to the infor­ma­tion sources that he or she follows.

While Google Reader does not pro­vide the same type of per­son­al­ized Hot List as Fever, it nonethe­less rep­re­sents an impor­tant web appli­ca­tion for data aggre­ga­tion. While Fever presents some com­pelling fea­tures, Google Reader is the dom­i­nant mar­ket leader for RSS read­ers. In February of 2007 this mar­ket share mea­sured 59% of the web-based RSS reader market.

With this dom­i­nant mar­ket share Google has inte­grated a sig­nif­i­cant toolset of social fea­tures into Google Reader. Most impor­tant are the per­son­al­iza­tion fea­tures that have been built into Google Reader. The two main aspects of this are the rec­om­men­da­tion engine and the indi­vid­ual social tools.

The most polit­i­cally com­pelling fea­ture of Google Reader is its rec­om­men­da­tion engine. Upon launch­ing the new fea­ture Beverly Yang, a Google employee, wrote,

to make it eas­ier to find inter­est­ing feeds, we’re mov­ing rec­om­men­da­tions into the new Explore sec­tion and giv­ing it a new name — “Recommended sources.” Like always, it uses your Reader Trends and Web History (if you’re opted into Web History) to gen­er­ate a list of feeds we think you might like.

Simply put, Google Reader has the abil­ity to track a user’s read­ing habits and use that as the basis for sug­gest­ing addi­tional con­tent either pop­u­lar across the web, or par­tic­u­larly inter­est­ing to that user’s inter­ests. This takes the bur­den of cat­e­go­riz­ing infor­ma­tion sources off of the user. Anyone can start with the infor­ma­tion sources that they know they want to read and par­tially rely upon Google Reader to find sim­i­lar sources from around the web.

Another impor­tant aspect of Google Reader’s fea­tures is its abil­ity to share and rec­om­mend items to peo­ple within your exist­ing social cir­cle. Google Reader allows users to share arti­cles with other users and to com­ment on these arti­cles when doing so. This allows for users to dis­cover new arti­cles and new sources of infor­ma­tion by either lever­ag­ing the algo­rithm behind Google’s rec­om­men­da­tion engine or through their social net­work of friends, cowork­ers, and contacts.

One final fea­ture impor­tant to keep in mind about Google Reader is the way it tracks a user’s read­ing habits and dis­plays this data in acces­si­ble charts. These read­ing trends allow any user to auto­mat­i­cally see which infor­ma­tion sources gar­ner their atten­tion most con­sis­tently. Ultimately the abil­ity to track read­ing habits with­out hav­ing to rely upon what one remem­bers read­ing can allow for a user to ana­lyze their own read­ing habits and per­haps restruc­ture their infor­ma­tion intake accordingly.

Overall, two key aspects of Fever and Google Reader are impor­tant to keep in mind for a dis­cus­sion their polit­i­cal poten­tial. Fever pro­vides analy­sis of infor­ma­tion sources already famil­iar to a per­son. This allows them to sort through mas­sive amounts of infor­ma­tion and lever­age an algo­rithm to fil­ter for impor­tance. Google Reader, then, pro­vides the abil­ity to use a social net­work of con­tacts as well as an algo­rithm to find new infor­ma­tion flows and news items. Most impor­tantly from a polit­i­cal stand­point, all of these tech­nolo­gies are able to used and struc­tured by an indi­vid­ual user. Individuals deter­mine the struc­ture of an infor­ma­tion flow in both Fever and Google Reader.

Translating aggre­ga­tion to politics

In a polit­i­cal sys­tem grounded in the involve­ment of the gen­eral pop­u­lace the rel­a­tive edu­ca­tion and knowl­edge of the cit­i­zenry is cru­cial to the legit­i­macy of the polit­i­cal deci­sions made. Thomas Jefferson rec­og­nized this when writ­ing “A Bill For The More General Diffusion of Knowledge.” In this he writes that,

even under the best forms, those entrusted with power have, in time, and by slow oper­a­tions, per­verted it into tyranny; and it is believed that the most effec­tual means of pre­vent­ing this would be, to illu­mi­nate, as far as prac­ti­ca­ble, the minds of the peo­ple at large.

Jefferson saw the edu­ca­tion of the cit­i­zenry as a foun­da­tional guard against the threat of tyranny. Having what he terms an illu­mi­nated cit­i­zenry is the best pro­tec­tion against unde­mo­c­ra­tic ele­ments that would oppress a peo­ple. Having the abil­ity to aggre­gate infor­ma­tion sources together using tools like Google Reader and Fever then pro­vides many oppor­tu­ni­ties for cit­i­zens to take the ini­tia­tive and inform them­selves of polit­i­cal mat­ters. The test of how well these tech­nolo­gies expand avenues for polit­i­cal par­tic­i­pa­tion, how­ever, relies heav­ily upon the abil­ity of users to fil­ter out the impor­tant infor­ma­tion from the irrel­e­vant noise.

In order for fil­ter­ing through online appli­ca­tions like Fever and Google Reader to be more effec­tive at inform­ing the cit­i­zenry than tra­di­tional media we need a solid tech­no­log­i­cal response to an online world in which the many can pub­lish. In The Wealth of Networks Yochai Benkler refers to early cri­tiques of the democ­ra­tiz­ing effects of infor­ma­tion online by describ­ing the Babel objec­tion. In Benkler’s words,

According to the Babel objec­tion, when every­one can speak, no one can be heard, and we devolve either to a cacoph­ony or to the reemer­gence of money as the dis­tin­guish­ing fac­tor between state­ments that are heard and those that wal­low in obscu­rity.2

A cacoph­ony in which all pub­lish but none con­sume would cer­tainly rep­re­sent an issue for a polit­i­cal sys­tem grounded in com­mon move­ments for change. In a demo­c­ra­tic polit­i­cal struc­ture where majori­ties, whether they be cit­i­zens or rep­re­sen­ta­tives, deter­mine deci­sions the abil­ity of peo­ple to con­verse with one another about top­ics of mutual con­cern is para­mount. In order for this con­ver­sa­tion to hap­pen we need some ele­ment of infor­ma­tion con­sump­tion; peo­ple need to have con­sumed infor­ma­tion to have a basis for dis­cus­sion. In short, we need con­sumers of infor­ma­tion and shar­ers of infor­ma­tion just as much as we need the publishers.

Despite the crit­i­cal impor­tance of ensur­ing the con­sump­tion of infor­ma­tion, Benkler views the cacoph­ony of an open pub­lish­ing world as not inher­ently debil­i­tat­ing. He writes that,

The Babel objec­tion may give us good rea­son to pause before we cel­e­brate the net­worked infor­ma­tion econ­omy, but it does not pro­vide us with rea­sons to cel­e­brate the auton­omy effects of the indus­trial infor­ma­tion econ­omy.3

While the con­cern over a world of pure pro­jec­tion is impor­tant it should not be so debil­i­tat­ing that it makes polit­i­cal life in the United States com­pla­cent. In a talk at the Web 2.0 Expo in New York in 2008 Clay Shirky points to those pro­claim­ing the dis­as­trous effects of a world in which every­body speaks as miss­ing the more sig­nif­i­cant, under­ly­ing prob­lem: the fil­ter. In this talk he says that,

Thinking about infor­ma­tion over­load isn’t actu­ally describ­ing the prob­lem and think­ing about fil­ter fail­ure is.

In an online real­ity where the many pos­sess the abil­ity to pub­lish the weight of keep­ing the pub­lic informed and, in Jefferson’s words, polit­i­cally effec­tual is not a prob­lem of too much infor­ma­tion, rather it is a prob­lem with a fil­ter that is not refined enough. With Google Reader and Fever we have tools that become increas­ingly more effec­tive at fil­ter­ing out the noise in infor­ma­tion streams and allow­ing cit­i­zens to more effi­ciently stay informed. By lever­ag­ing the rec­om­men­da­tions detailed above, Fever’s link analy­sis or Google Reader’s socially-powered rec­om­men­da­tions, it becomes eas­ier for peo­ple to take in a wide array of infor­ma­tion and fil­ter it for the most polit­i­cally impor­tant and rel­e­vant material.

A final aspect of aggre­ga­tion tech­nol­ogy that improves the poten­tial avenues of polit­i­cal par­tic­i­pa­tion is the way that Google Reader, Fever, and any other RSS reader pools together var­i­ous sources into a sin­gle, con­tained infor­ma­tion flow. In an infor­ma­tion econ­omy where print sig­ni­fies the most tech­no­log­i­cal option avail­able infor­ma­tion comes to peo­ple in dis­tinct pack­ets. The raw form can come in pri­mary source doc­u­ments that present some­thing closer to plain data while the aggre­ga­tion hap­pens through sec­ondary source mate­r­ial where the author must care­fully aggre­gate and curate the infor­ma­tion ref­er­enced. Data aggre­ga­tion through RSS places this power in the hands of the peo­ple. Any indi­vid­ual can sub­scribe to feeds of var­i­ous news or data sources and have all of that infor­ma­tion flow into a cen­tral repos­i­tory. Lastly, when com­bined with the type of rec­om­men­da­tions and social fea­tures from Google Reader or the Hot List fea­ture of Fever this places the power of find­ing rela­tion­ships between infor­ma­tion sources in the con­trol of an indi­vid­ual. Each indi­vid­ual who uses a tool of data aggre­ga­tion can com­pare var­i­ous sources to find sim­i­lar­i­ties, dif­fer­ences, and con­tra­dic­tions. Ultimately it greatly increases indi­vid­ual auton­omy by allow­ing each per­son to receive infor­ma­tion straight from the source and serve as their own fil­ter with­out hav­ing to trust in the fil­ter­ing abil­i­ties of a third party.

Aggregated Participation

Aggregated raw infor­ma­tion and infor­ma­tion rec­om­men­da­tions from a per­sonal social cir­cle and a refined algo­rithm expand the poten­tial infor­ma­tion to which each per­son has access. Individuals can now per­son­al­ize an infor­ma­tion flow and lever­age their wide rang­ing social net­works, as well as the skills of soft­ware devel­op­ers, to find addi­tional sources of data. All of this serves an impor­tant func­tion for expand­ing access to data and infor­ma­tion, both of which serve as key foun­da­tional ele­ments to polit­i­cal par­tic­i­pa­tion in the United States. These tech­nolo­gies can pro­vide some­thing greater though as well. Not only can they aggre­gate infor­ma­tion and increase the infor­ma­tion flows used as a basis for par­tic­i­pa­tion but they can also aggre­gate and fil­ter participation.

The acts of polit­i­cal par­tic­i­pa­tion occur­ring through the real-time web com­bine with the mat­u­ra­tion of self-publishing tools and advanced aggre­ga­tion tech­nol­ogy to pro­vide a pow­er­ful rede­f­i­n­i­tion of pub­lic polit­i­cal par­tic­i­pa­tion. This def­i­n­i­tion hinges upon indi­vid­ual activ­ity aggre­gated in the col­lec­tive to find rela­tion­ships between opin­ions that help spur polit­i­cal action.

The most impor­tant aspect of being able to aggre­gate expressed polit­i­cal opin­ions using these tech­nolo­gies is the acces­si­bil­ity of these tools to the indi­vid­ual. As Dave Winer, one of the found­ing devel­op­ers behind RSS, says in the afore­men­tioned BBC arti­cle,

RSS makes it pos­si­ble for infor­ma­tion to flow to you.

The con­tent of this infor­ma­tion can be any­thing but ulti­mately it all flows to a sin­gle indi­vid­ual who then can make judge­ments based upon it. This is not polit­i­cal infor­ma­tion stream­ing through an inter­est group’s fil­ter. It is not news being restricted to what passes the main­stream media fil­ter. It is not polit­i­cal opin­ion com­ing down to cit­i­zens from a pre­sum­ably trust­wor­thy rep­re­sen­ta­tive. Rather, it is infor­ma­tion flow­ing directly to those who ulti­mately have to make polit­i­cal deci­sions: individuals.

The inde­pen­dence of indi­vid­ual judge­ment and infor­ma­tion intake is impor­tant for par­tic­i­pa­tion to effec­tively be extended to a mass of indi­vid­ual cit­i­zens. By allow­ing indi­vid­u­als to aggre­gate their own infor­ma­tion and come to their own judge­ments con­cern­ing it the polit­i­cal sys­tem can become reflec­tive of what indi­vid­u­als actu­ally desire from their gov­ern­ment. Instead of rely­ing upon a mass media out­let to aggre­gate and curate infor­ma­tion users can now use some­thing like Fever’s Hot List to inde­pen­dently view what the impor­tant sto­ries of the day, week, or month are. Furthermore, with all of the social fea­tures pack­aged into Google Reader any user of that RSS reader could quickly and eas­ily lever­age his or her exist­ing social net­work to inform their decisions.

Finally, all of this indi­vid­ual con­trol over infor­ma­tion con­sump­tion con­tributes to a polit­i­cal arena in which indi­vid­u­als are actu­ally informed about the polit­i­cal actions they take. Information plays a cen­tral role in polit­i­cal actions. Whether that action is orga­niz­ing a move­ment for polit­i­cal change, vot­ing for a can­di­date, or sim­ply dis­cussing polit­i­cal issues over with fam­ily mem­bers infor­ma­tion lies at the cen­ter of every­thing. The ways in which indi­vid­u­als gather and sort this infor­ma­tion sig­nals an inher­ently polit­i­cal act. That infor­ma­tion informs polit­i­cal par­tic­i­pa­tion and discussion.

By plac­ing the onus of informed par­tic­i­pa­tion upon the indi­vid­ual these tools allow for indi­vid­u­als to come to their own con­clu­sions con­cern­ing infor­ma­tion. A greater reliance upon a per­son­ally cus­tomized river of infor­ma­tion means that indi­vid­u­als can come to rely upon other pack­aged ver­sions of infor­ma­tion less. By cut­ting out a mid­dle step of inter­pre­ta­tion indi­vid­u­als can learn to process ideas and knowl­edge them­selves in such a way that it informs their par­tic­i­pa­tion in politics.

For a democratically-based polit­i­cal sys­tem like the United States the free­dom and inde­pen­dence of indi­vid­u­als is vitally impor­tant. Modern tools of data aggre­ga­tion like Fever and Google Reader pro­vide the abil­ity for peo­ple to take a faster flow­ing stream of data pub­lished by the many and turn it into their own, inde­pen­dent source for informed participation.

  1. This process is effec­tively explained in a 2005 arti­cle pub­lished by the BBC.
  2. Benkler, 10.
  3. Benkler, 171.