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• Social Proof: A Tool for Determining Authority

  by Steve McCann

  April 15, 2009
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  In the Library with the Lead Pipe is pleased to wel­come another guest
  author, Steve McCann! Steve is a Dig­i­tal Projects Librar­ian spe­cial­iz­ing in infor­ma­tion archi­tec­ture, usabil­ity stud­ies, and data analysis.

  In 2008, when I was vis­it­ing Ana­heim, CA, for the ALA Annual Con­fer­ence, I had a rather unpleas­ant expe­ri­ence rent­ing a car. I had a reser­va­tion for the least expen­sive vehi­cle avail­able (gas at that time was priced around $4 a gal­lon), but the sales­man was insist­ing I upgrade to some­thing larger. What sticks out in my mem­ory was the tac­tic he was using, an influ­ence tech­nique called Social Proof which I had been read­ing about. His gam­bit was to point to an SUV on his pic­to­r­ial list of avail­able cars and emphat­i­cally state that “this is what every­one is rent­ing here in Los Ange­les.” This put me in an awk­ward posi­tion, since the idea that 100% of car rentals in LA were over­sized SUVs was some­thing I sim­ply hadn’t con­sid­ered pre­vi­ously. I found myself in a state of insuf­fi­cient infor­ma­tion and was sus­pi­cious that he was try­ing to take advan­tage of this. In fact, he was claim­ing author­ity on the sub­ject of cor­rect LA car rental pro­ce­dures, and I could either accept his author­ity or go against “every­one” and rent a sub­com­pact. It was a strange sit­u­a­tion for a librar­ian to find him­self, since I am, in gen­eral, much more likely to be nav­i­gat­ing a state of “infor­ma­tion over­load.” If I had thought of it, I could have con­sulted my Inter­net friends via my cell phone and got­ten a plethora of advice, but, in the end, I knew the whole idea was silly so I declined. Unde­terred, he said his piece again, only this time much more loudly as if I couldn’t hear him. After declin­ing a sec­ond time, I received a remark­able look of dis­gust, remind­ing me strongly of some­one bit­ing into a lemon.

  I bring up this story because of the vis­ceral power of this type of coer­cion. For me, it was patently obvi­ous that he could not back up the claims he was mak­ing so, in a sense, I had it easy. His asser­tion lacked cred­i­bil­ity at a gut level, and I really didn’t need to con­sult with any­one else. Reflect­ing on the sit­u­a­tion, how­ever, it became appar­ent that stand­ing at the rental counter sur­rounded by unfa­mil­iar peo­ple and ask­ing for a vehi­cle was, in a way, anal­o­gous to the expe­ri­ence a patron has when vis­it­ing a ref­er­ence desk for the first time. They obvi­ously have an infor­ma­tion prob­lem and are look­ing for an author­ity of some kind. The main dif­fer­ence is that a ref­er­ence librar­ian is trained to help patrons locate cred­i­ble author­i­ties in spite of a thicket of fed­er­ated searches, Library of Con­gress call num­bers, sub­ject terms, and the spec­trum of “arti­cle — jour­nal — data­base” resources, among count­less other dif­fi­cul­ties. The librar­ian is an author­ity in her own right on the sub­ject of research and gen­er­ally rec­og­nized as such. The ques­tion this arti­cle seeks to ask is: to what extent can the library web­site frame­work, with all of its cat­a­logs, ven­dors, guides, etc., become rec­og­nized as an author­ity in the sub­ject of research? The assump­tion I am mak­ing is that library web­sites are not auto­mat­i­cally deemed author­i­ties by patrons in the same way that librar­i­ans them­selves are. First, many of our patrons con­sult with more rec­og­nized author­i­ties in the form of Google ser­vices, the home pages of jour­nal titles, or even, maybe espe­cially, other patrons. In this arti­cle I pro­pose that what library web­sites are miss­ing is evi­dence of “social proof.” I will then intro­duce a com­mer­cial ser­vice that is tak­ing steps in this direc­tion with regard to weblogs and finally brain­storm the type of changes that would be required to sup­ply this evidence.

  How We Rec­og­nize Authority

  “What we’re deal­ing with now isn’t infor­ma­tion over­load […] it really is a fil­ter­ing prob­lem rather than an infor­ma­tion [prob­lem].” (Shirky, 2008)

  “One of the cri­te­ria we use to fil­ter infor­ma­tion is cred­i­bil­ity, or believ­abil­ity.” (Wathen, 2002)

  Patrick Wil­son (1983), in his book Sec­ond Hand Knowl­edge, makes the dis­tinc­tion between two types of author­ity, admin­is­tra­tive and cog­ni­tive. The first has power to com­mand, but the sec­ond has power to influ­ence one’s thoughts. Think­ing back on the ear­lier exam­ple of the rental car sales­man, the rea­son I wasn’t influ­enced was because he sim­ply wasn’t cred­i­ble. As it turns out, cred­i­bil­ity is a major com­po­nent of cog­ni­tive author­ity along with trust­wor­thi­ness, reli­a­bil­ity, schol­ar­li­ness, “offi­cial­ness,” and author­i­ta­tive­ness (Rieh, 2002). If a per­son, entity, or idea can achieve an impres­sion of qual­ity in any of these six areas, then that entity can act as a cog­ni­tive author­ity. The impor­tant point is that cred­i­bil­ity and author­ity are both per­cep­tions: a recog­ni­tion of a qual­ity which, once made, will allow a per­son to place her trust in a fig­ure of per­ceived author­ity.  Once placed, that recog­ni­tion labels a per­son or idea as some­one who “knows some­thing we do not know” and who “knows what they are talk­ing about” (Wil­son, 1983).

  The ques­tion then becomes what fac­tors influ­ence this per­cep­tion of cog­ni­tive author­ity? In the fol­low­ing list, Wathen and Burkell (2002) sum­ma­rize the vari­ables related to per­cep­tion into five fac­tors affect­ing credibility:

  1. Source mate­r­ial
     1. Exper­tise / Knowledge
     2. Trust­wor­thi­ness
     3. Cre­den­tials
     4. Attrac­tive­ness
     5. Sim­i­lar­ity
     6. Like­abil­ity / Good­will / Dynamism
  2. Receiver of material
     1. Rel­e­vance
     2. Moti­va­tion
     3. Prior knowl­edge
     4. Involve­ment
     5. Val­ues / beliefs / situation
     6. Stereo­types about source or topic
     7. “Social loca­tion”
  3. Mes­sage
     1. Topic / content
     2. Inter­nal valid­ity / consistency
     3. Plau­si­bil­ity of arguments
     4. Sup­ported by data or examples
     5. Fram­ing (loss or gain)
     6. Rep­e­ti­tion / familiarity
     7. Order­ing
  4. Medium of the material
     1. Orga­ni­za­tion
     2. Usabil­ity
     3. Pre­sen­ta­tion
     4. Vivid­ness
  5. Con­text of the information
     1. Dis­trac­tion / “noise”
     2. Time since mes­sage encountered
     3. Degree of need

  What is strik­ing about this list is that it is an awfully large num­ber of judg­ments for a stu­dent to make. Work­ing on the ref­er­ence desk, it’s not uncom­mon for a stu­dent to say he or she has a paper due that day and needs three author­i­ta­tive sources. The stu­dent in this sit­u­a­tion is not going to con­duct a sys­tem­atic search but rather resort to a more prim­i­tive form of deci­sion mak­ing, Social Proof.

  The Power of Social Proof

  “The indi­vid­ual can be con­cep­tu­al­ized as a social actor, and information-seeking activ­i­ties take place within a social com­mu­nity whose knowl­edge, char­ac­ter­is­tics, expec­ta­tions, and norms are inter­nal­ized within the indi­vid­ual. This may be espe­cially rel­e­vant for young peo­ple, whose infor­ma­tion seek­ing and learn­ing is inher­ently social given the impor­tance of social ties and net­works dur­ing ado­les­cence and early adult­hood” (Rieh, 2008).

  In Cialdini’s (1988) Influ­ence: the Psy­chol­ogy of Per­sua­sion, he talks about the enor­mous power of Social Proof. Here’s the car­toon ver­sion found on page 120 (it may remind you strongly of how Digg, Deli­cious, and other social tag­ging sys­tems work):

   

  

  Fig­ure 1: The Pow­er­ful Affect of Sim­i­lar Oth­ers on our Behav­ior (Cial­dini, 1988)

  Accord­ing to Cial­dini (1988), what’s going on in the image above is the “awe­some influ­ence of the behav­ior of sim­i­lar oth­ers.”  In other words, one impor­tant tool we use to decide how to act in a given sit­u­a­tion is to look at what other peo­ple are doing. It may be that this is an evo­lu­tion­ary byprod­uct. For exam­ple, if some­one stands up calmly in a crowded library com­puter lab and yells “fire!” and then sits down again, the chances are good that you will work your way through a check­list of cred­i­bil­ity fac­tors. Is the source cred­i­ble? Is the infor­ma­tion rel­e­vant to me? Is the mes­sage plau­si­ble? Was the pre­sen­ta­tion con­vinc­ing? Isn’t this just juve­nile noise? If the stu­dent who yelled goes back to work, then his cred­i­bil­ity is sus­pect and evac­u­a­tion is unlikely. How­ever, if the two fac­tors of uncer­tainty and sim­i­lar­ity are at play, then cred­i­bil­ity is judged very quickly. Uncer­tainty can be described as the state “when we are unsure of our­selves, when the sit­u­a­tion is unclear or ambigu­ous[.] When uncer­tainty reigns, we are most likely to look to and accept the actions of oth­ers as cor­rect” (Cial­dini, 1988).  Are peo­ple start­ing to leave the com­puter lab? If yes, then the per­cep­tion of cred­i­bil­ity just got a big boost. This per­cep­tion is espe­cially strong if the other peo­ple in the lab are viewed as sim­i­lar to ourselves.

  This behav­ior trans­fers quite well to the web. For exam­ple, in eye-tracking stud­ies of mar­ket­ing mate­ri­als it is con­sis­tently shown that peo­ple look where other peo­ple are look­ing. The fol­low­ing heatmap images from a eye-tracking study shows this quite clearly (Breeze, 2009):

   

  

  Fig­ure 2: The Effects of Social Proof in Advertising

  “Here’s the same 106 peo­ple look­ing at the sec­ond image for the same amount of time […] Notice how many more peo­ple are actu­ally read­ing the text that the baby is look­ing at in the above image? Not to men­tion the increased atten­tion on the brand!”

  The rea­son this behav­ior is sig­nif­i­cant is because stud­ies have shown peo­ple will read, at most, 28% of the words on a web page (Nielsen, 2008). The author of the above eye track­ing study is say­ing that peo­ple are actu­ally read­ing the text, but it’s clear that they are not read­ing the entire text. They are just skim­ming and key­ing in on cer­tain key­words such as “chlorine-free” and “clin­i­cally.” In an eye-tracking heatmap like the one above, the more con­cen­trated the col­ors over a text, the more time is being spent look­ing at that area of the screen. In short, mar­keters are able to manip­u­late the effects of social proof to force peo­ple to stop and read their copy.

  But let’s return to the sub­ject of library web­sites. How can we con­vince users to pay atten­tion to fac­tors of cred­i­bil­ity? Library inter­faces are largely text based. Take a look at most OPACs, and it’s clear that this type of short-circuiting of cred­i­bil­ity judg­ments is not hap­pen­ing. Instead, libraries are rely­ing on the users tak­ing a labo­ri­ous and sys­tem­atic approach by judg­ing between mul­ti­ple cred­i­bil­ity fac­tors. In a sense this is wholly cor­rect; librar­i­ans are invested in sup­ply­ing the user with texts that are not only grat­i­fy­ing but also appro­pri­ate. Librar­i­ans are also invested in teach­ing the care­ful eval­u­a­tion of the cred­i­bil­ity fac­tors of those sources. On the other hand, in the image above the mar­keter asserts the text the baby is look­ing at is the right text; the brand being pre­sented is the right brand to sat­isfy the consumer’s infor­ma­tion need.  Librar­i­ans would not make such a claim because we rec­og­nize more than most the immense num­ber of con­tex­tual vari­ables involved. In this way library web­sites are largely designed around a con­tra­dic­tion: on the one hand we assert that a solu­tion to an infor­ma­tion need can be found within our domains; but on the other hand we refuse to make any judg­ments regard­ing the cred­i­bil­ity of texts for our users. The ques­tion then becomes is this atti­tude a mis­take? Is it not pos­si­ble that some form of visual cred­i­bil­ity rank­ing could be found to bridge this gap?

  The Pos­tRank Model

  One com­pany is com­bin­ing the prin­ci­ples of social proof along with a more for­mal­ized approach to the rank­ing of cred­i­bil­ity. The way they are doing it is instruc­tive for librar­i­ans, even if the amount of data pro­cess­ing involved is daunt­ing. As of this writ­ing they are cur­rently rank­ing the social proof for nearly 900,000 RSS feeds. The total num­ber of indi­vid­ual weblog post­ings comes to approx­i­mately 1.6 mil­lion per day. For each of these feeds, they then track the social per­for­mance of each post rel­a­tive to other posts within the same RSS feed. The social met­rics used to cal­cu­late this per­for­mance they are call­ing the “Five C’s of Engage­ment:” Cre­at­ing, Cri­tiquing, Chat­ting, Col­lect­ing, and Click­ing. The the­ory behind this is one of social proof: the more an indi­vid­ual weblog post is inter­acted with socially, the more atten­tion it prob­a­bly war­rants. Fig­ure 3 is an exam­ple of the Pos­tRank score for recent arti­cles pub­lished in Smash­ing Mag­a­zine, a usabil­ity and design weblog. Notice that low-scoring posts are grayed out, the good-scoring post is light orange (score = 5.6), and the best-scoring post is a dark orange. “Cred­i­bil­ity” is imme­di­ately rec­og­niz­able in the sec­ond post which scored a 7.3.

   

  

  Fig­ure 3: Smash­ing Mag­a­zine arti­cles fil­tered to show only “Good” postings.

   

  When the user hov­ers over this score they are pre­sented with a visual break­down of the com­po­nent fac­tors that go into this cred­i­bil­ity rank­ing (fig­ure 4). Each fac­tor rep­re­sents a social activ­ity score from PostRank’s “5 C’s of Engagement.”

   

  

  Fig­ure 4: Break­down of com­po­nent fac­tors that com­bined to cre­ate the Pos­tRank score.

   

  The imple­men­ta­tion of Pos­tRank scores is highly volatile, which has caused some to ques­tion its use­ful­ness. For exam­ple, after check­ing the three Pos­tRank scores 24 hours fol­low­ing the image cap­ture of Fig­ures 1 & 2, the scores had already changed. The com­pany uses a mov­ing tem­po­ral win­dow in which all posts are cal­cu­lated one against the other. An exam­ple of the effect this causes is if your weblog pub­lishes a sin­gle post that is then “slash­dot­ted” (i.e., sud­denly wildly pop­u­lar because of a men­tion in a high-traffic web­site) then all other posts in that tem­po­ral win­dow will sud­denly score extremely low because of the dif­fer­ence in social activ­ity between the post­ings. This scor­ing dis­crep­ancy will remain until the tem­po­ral win­dow passes the high-performing post, or until the low-performing posts them­selves are sup­planted by a new higher stan­dard of per­for­mance. While this may or may not make sense from a busi­ness stand­point, from the user’s point of view rank­ings that jump around fre­quently affects the per­ceived “trust­wor­thi­ness” of the rank­ing system.

  Ele­ments of Social Proof for Library Websites

  If library web­sites were able to develop such a tool with which to rank the cred­i­bil­ity / cog­ni­tive author­ity of all the intel­lec­tual con­tent within their domains, what would it look like? Because of the librarian’s call­ing to pro­vide access to, but not judg­ment of, the indi­vid­ual texts, it would have to take into account the cred­i­bil­ity fac­tors iden­ti­fied above. To work in the highly social envi­ron­ment of the web, the library web­site would also need to put the power of social proof into play. The web­site would need to be designed in a way as to allow patrons to quickly and visu­ally iden­tify the atten­tion of “sim­i­lar oth­ers.” In other words,the true cog­ni­tive author­i­ties within any given sub­ject. To meet these con­flict­ing demands, the tool would need to pro­vide feed­back in the two areas where social proof is strongest: Uncer­tainty and Similarity.

  To com­bat a user’s “uncer­tainty” when nav­i­gat­ing between mul­ti­ple source mate­ri­als, our tool would need to show ele­ments that assist in snap judg­ments. This would involve data that is super­fi­cial to the con­tent of a work, or, accord­ing to Tseng & Fogg ele­ments of pre­sumed cred­i­bil­ity and sur­face cred­i­bil­ity (Tseng, 1999).

  • Uncer­tainty Data Elements
    • Cita­tion counts and/or incom­ing links to a work
    • Num­ber of times a work was checked out or read
    • Num­ber of works an author has pub­lished in her career
    • Num­ber of com­ments attached to a work
    • The attrac­tive­ness, like­abil­ity, and/or usabil­ity of the work’s format

  To deter­mine “sim­i­lar­ity,” our tool would need to show ele­ments that assist the user to make a judg­ment as to the cog­ni­tive author­ity of a work. This would involve source labels such as “PhD,” the title of the jour­nal, the name of the pub­lish­ing com­pany, etc. Other sim­i­lar­ity scores might include the expe­ri­ence other schol­ars had with the work or even per­sonal rat­ings like what is seen in GoodReads. Accord­ing to Tseng & Fogg, these ele­ments would be com­posed of reputed cred­i­bil­ity and expe­ri­enced cred­i­bil­ity fac­tors.

  • Sim­i­lar­ity Data Elements
    • Source impact fac­tors of a title or journal
    • Source rejec­tion rate of a jour­nal title or publisher
    • Whether or not the work is refereed
    • The total num­ber of crit­i­cal reviews
    • The cal­cu­lated qual­ity of works cit­ing the work in question
    • The Library of Con­gress sub­ject terms asso­ci­ated with the work
    • Tem­po­ral group­ings; an exam­ple might be a 10 year, 100 year, or adjustable win­dow that affects all ele­ment calculations
    • Total num­ber of syl­labi listings
    • Total num­ber of sub­scribers to a peri­od­i­cal title or hold­ings cal­cu­la­tion for other works
    • A user gen­er­ated “thumbs up” or “thumbs down” ranking

  The series of cal­cu­la­tions involved for each title in the above fac­tors could then be rep­re­sented within a library OPAC or a peri­od­i­cals data­base in a way sim­i­lar to that of PostRank’s sys­tem. If it was built cor­rectly it could be used to quickly and eas­ily “drill down” to rel­e­vant cog­ni­tive author­i­ties within any given research con­text. Of course there is a poten­tial down­side. The first is the immense amount of data that would have to be man­aged on an ongo­ing basis. The sec­ond, and per­haps more press­ing, would be the prob­lem of unin­tended con­se­quences. Just because a piece of infor­ma­tion is socially dynamic, doesn’t mean that it is cor­rect or even help­ful. A cau­tion­ary tale from the world of finance involves the below chart high­light­ing the finan­cial bub­ble which peaked in 2006/2007. In fig­ure 5, the ana­lyst Barry Ritholtz (lower left) rec­og­nized early on that the fun­da­men­tals of the econ­omy did not sup­port the high val­u­a­tion of stocks. He was proven cor­rect, but not until the mar­ket col­lapsed in 2008/2009.

  

  Fig­ure 5: Herd Men­tal­ity Shown Among Analysts

  This type of herd men­tal­ity is a hall­mark of social proof. To make mat­ters worse, there is no proof that the ele­ments I’ve selected above would be the cor­rect ones for the researcher’s infor­ma­tion needs. It is uncer­tain whether such a cred­i­bil­ity rank­ing sys­tem would lead to more harm than good.

  Con­clu­sion

  In this arti­cle, I’ve attempted to brain­storm a method for rais­ing the pro­file of library web­sites to the level of author­ity that indi­vid­ual librar­i­ans enjoy. To do this, mul­ti­ple cred­i­bil­ity fac­tors will need to be addressed and social proof feed­back will need to be imple­mented in some way. Despite its flaws, the Pos­tRank model may pro­vide guid­ance on how this could be accom­plished. It would be cal­cu­la­tion inten­sive and require iter­a­tive research to make sure it was not skew­ing patron’s sense of cred­i­bil­ity within sub­ject areas. But regard­less of the dif­fi­cul­ties, it may be help­ful to remem­ber what a sta­tis­tics pro­fes­sor has said about rely­ing upon mod­els for guid­ance: all mod­els are wrong, but some mod­els are useful.

  Thanks to Derik Bad­man, Jen­nie Bur­roughs, Ellie Col­lier, Donna McCrea, and Sue Sam­son for their assis­tance in review­ing and edit­ing this arti­cle. Spe­cial thanks to Kim Duck­ett whose feed­back on my ear­lier work on social proof and author­ity led me to write this article.

  Bib­li­og­ra­phy

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  Rieh, S. Y., and N. J. Belkin. 1998. Under­stand­ing judg­ment of infor­ma­tion qual­ity and cog­ni­tive author­ity in the WWW. Jour­nal of the Amer­i­can Soci­ety for Infor­ma­tion Sci­ence 35, 279 – 289.

  Rieh, Soo Y., and Brian Hilligoss. 2007. Col­lege Stu­dents’ Cred­i­bil­ity Judg­ments in the Information-Seeking Process. The John D. and Cather­ine T. MacArthur Foun­da­tion Series on Dig­i­tal Media and Learn­ing -, 49 – 71.

  Ritholtz, Barry. Cult of the Bear, Part 1. in TheStreet​.com. 2006 [cited April 14 2009]. Avail­able from http://​www​.thestreet​.com/​_​t​s​c​a​n​a​/​m​a​r​k​e​t​s​/​m​a​r​k​e​t​f​e​a​t​u​r​e​s​/​1​0​2​6​0​0​9​6​.​h​tml.

  Savolainen, R. Media cred­i­bil­ity and cog­ni­tive author­ity. The case of seek­ing ori­ent­ing infor­ma­tion. Infor­ma­tion Research: an inter­na­tional elec­tronic jour­nal 12.

  Shirky, Clay. 2008. It’s Not Infor­ma­tion Over­load. It’s Fil­ter Fail­ure. Web 2.0 Expo 2008. New York, NY ed.O’Reilly Media, Inc. and Tech­Web. Avail­able from http://​www​.web2​expo​.com/​w​e​b​e​x​n​y​2​0​0​8​/​p​u​b​l​i​c​/​s​c​h​e​d​u​l​e​/​d​e​t​a​i​l​/​4​817

  Sun­dar, S. S. 2007. The MAIN Model: A Heuris­tic Approach to Under­stand­ing Tech­nol­ogy Effects on Cred­i­bil­ity. The John D. and Cather­ine T. MacArthur Foun­da­tion Series on Dig­i­tal Media and Learn­ing -, 73 – 100.

  Wathen, C. N., and J. Burkell. 2002. Believe it or not: Fac­tors influ­enc­ing cred­i­bil­ity on the Web. Jour­nal of the Amer­i­can Soci­ety for Infor­ma­tion Sci­ence and Tech­nol­ogy 53, no. 2:134 – 144.

  Wein­garten, Fred W. 2007. Cred­i­bil­ity, Pol­i­tics, and Pub­lic Pol­icy. The John D. and Cather­ine T. MacArthur Foun­da­tion Series on Dig­i­tal Media and Learn­ing -, 181 – 202.

  Wil­son, P. 1983. Second-hand knowl­edge: An inquiry into cog­ni­tive author­ity. Green­wood Pub Group.

  Work­man, M. 2008. Wise­crack­ers: A theory-grounded inves­ti­ga­tion of phish­ing and pre­text social engi­neer­ing threats to infor­ma­tion secu­rity. Jour­nal of the Amer­i­can Soci­ety for Infor­ma­tion Sci­ence and Tech­nol­ogy 59, no. 4.
  

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  Tags: authority, library websites, PostRank, social proof

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8 Comments

• Peter Murray says:

  April 15, 2009 at 8:37 am

  You missed the cita­tion for Shirky’s infor­ma­tion fil­ter­ing quote in the bib­li­og­ra­phy. I was won­der­ing if it was his “It’s Not Infor­ma­tion Over­load. It’s Fil­ter Fail­ure” talk at the Web 2.0 Expo last year. I wrote about that in my own blog. I’m ask­ing because I’m inter­ested to see if he devel­oped this notion fur­ther than he took it in that presentation.

  Reply
• Steve McCann says:

  April 15, 2009 at 9:07 am

  Thanks Peter, you’re right that is where I found the quote. We’ll try to get the post updated, but in the mean­time here’s the citation:

  Shirky, Clay. 2008. It’s Not Infor­ma­tion Over­load. It’s Fil­ter Fail­ure. Web 2.0 Expo 2008. New York, NY ed.O’Reilly Media, Inc. and Tech­Web. Avail­able from http://​www​.web2​expo​.com/​w​e​b​e​x​n​y​2​0​0​8​/​p​u​b​l​i​c​/​s​c​h​e​d​u​l​e​/​d​e​t​a​i​l​/​4​817

  It’s a great notion and I’m sur­prised he hasn’t pub­lished it any­where (as far as I can tell).

  Reply
• Melanie Baker says:

  April 17, 2009 at 1:48 pm

  Hi Steve,

  What an engag­ing read — my com­pli­ments (and thank you for includ­ing Pos­tRank). :) Par­tic­u­larly inter­est­ing to me since, as you can imag­ine, we spend a LOT of time talk­ing among our­selves and with the user com­mu­nity about the nature of author­ity, influ­ence, and engage­ment. Fas­ci­nat­ing to be involved in an envi­ron­ment while we’re try­ing to write def­i­n­i­tions for things we’re immersed in daily.

  A cou­ple of clar­i­fi­ca­tions about how Pos­tRank works. Pos­tRank scores change quickly because the met­rics are gathered/analyzed in real-time.

  So when a post is just pub­lished, no one’s engaged with it yet, so it’ll score a 1.0. But as soon as peo­ple start engag­ing with it — com­ments, book­marks, tweets, etc. — its score starts to rise (com­pared with the per­for­mance of other recent posts on the site).

  If the scor­ing didn’t change with the met­rics, the scores wouldn’t be accu­rate or very use­ful. And if they didn’t change very fast they wouldn’t be very use­ful to those who must reg­u­larly monitor.

  Not to men­tion the fact that ~50% of posts’ engage­ment hap­pens within the first 50 min­utes post-publishing, and you can’t engage with your audi­ence while the con­ver­sa­tions are going on if you don’t know where and when.

  Of course, at the same time, we don’t con­tinue to check for met­rics indef­i­nitely, but have cal­cu­lated an engage­ment curve to deter­mine typ­i­cal engage­ment veloc­ity of posts.

  Sec­ondly, we’re def­i­nitely aware of the digg/slashdot/re-tweet/insert-your-own-viral-experience effect, and so have made sure to weight for it in our algorithms.

  If we didn’t, as you noted, it would tor­pedo the rank­ings of posts in a sim­i­lar time frame and would make the rank­ings about as bal­anced as me com­par­ing my blog’s engage­ment to TechCrunch’s. (Which is why we don’t com­pare to other sites, either, in deter­min­ing a site’s posts’ metrics.)

  Hope that helps. If any of that isn’t clear, or you have any ques­tions, feel free to let me know.

  Reply
• L. D. Mitchell says:

  April 24, 2009 at 11:52 am

  This might help explain the con­tin­u­ing dis­con­nect between library USAGE and library FUNDING, as reported in the ALA’s most recent State of America’s Libraries report.…

  Reply
• James Breeze says:

  May 9, 2009 at 7:01 am

  Thanks for the reference!

  You present an inter­est­ing and com­plex per­spec­tive. I am keen to do some more think­ing about this in order to cre­ate a set of guide­lines on cre­at­ing social media.

  From the social per­spec­tive, it would seem that the per­ceived cred­i­bil­ity of a per­son on Twit­ter, for exam­ple, strongly affects the like­li­hood that they would be fol­lowed. ‘Fol­low­ing’ some­one is a judge­ment based on the follower/followed ratio, user pro­file text, pres­ence of a pro­file link, the graph­ics of the Twit­ter pro­file page and con­tent of the tweets vis­i­ble on a the page at the time it is seen. Not to men­tion the fact that some­one is well known then they are likely to get a lot of followers.

  It is also inter­est­ing to note with Twit­ter, the herd men­tal­ity is not as sim­ple as it seems. If you have a lot of followers/following then a judge­ment must be made on why this is so? Are you sim­ply mar­ket­ing or are you actu­ally popular?

  Reply
• Social Proof: A Tool for Determining Authority — cafedave.net says:

  May 11, 2009 at 8:37 pm

  […] Social Proof: A Tool for Deter­min­ing Author­ity — a librar­ian dis­cusses how it might be pos­si­ble to apply offline meth­ods for deter­min­ing trust in a source to web­sites and other online phe­nom­ena. With bibliography! […]

  Reply
• Emily Ford says:

  May 15, 2009 at 3:00 pm

  I’m com­ing to your post a month late now, but I just wanted to say a big thank you for this article!

  The whole idea is fas­ci­nat­ing to me. Do you have exam­ples of library web sites/systems that are imple­ment­ing any form of social proof at this point? Has any­thing been shown or are there any case stud­ies that have been done for library sites or OPACs that have “favorites” or reviews enabled within the system?

  This also reminds me of the EBay exam­ple of social proof. How do we choose from which ven­dor to pur­chase? Well, we choose those who have the best user ratings.

  I under­stand you’re talk­ing here about a more tech­no­log­i­cal model of social proof, but the idea comes from the same place.

  Great post!

  Reply
• Steve McCann says:

  May 15, 2009 at 4:59 pm

  Thanks Emily, I think you’re right about the EBay model of user rat­ings help­ing us decide lev­els of sat­is­fac­tion. That’s social proof at it’s most ele­men­tal, imho. I don’t know of any libraries that are doing it with data, but with images many are (or should be). A quick Google Image search brings up the fol­low­ing exam­ples of Cialdini’s “pow­er­ful influ­ence of sim­i­lar oth­ers”:
  Smil­ing Sub­ject Mat­ter
  Some­thing to pay atten­tion to
  Phys­i­cal research
  Library web­site research
  Busy pub­lic library
  Busy aca­d­e­mic library
  Library as place
  Really good “library as place”

  Reply