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.