5 opportunities around social networks

In pre­vi­ous entries, I looked at the ben­e­fits and issues with social net­works. As they move for­ward, here’s a list of oppor­tu­ni­ties relat­ing to social networks. 

5. Data Mining/Research

A main attribute of social net­works is how much data peo­ple pro­vide to them. On top of it, this data and the inter­ac­tion of users on those net­works. This is rich fod­der for data min­ing. For exam­ple, researchers recently used Where’s George, a web­site track­ing dol­lar bills in the real world, to assess how dis­ease spreads. Sim­i­larly, LinkedIn pro­vides its users with demographic/geographic data about mem­bers of your social network.

Tra­di­tional com­pa­nies spend mil­lions of dol­lars try­ing to under­stand the flow of peo­ple, flow of ideas (or memes) and how to exploit them. From Milgram’s small world exper­i­ment to the suc­cess of “The Tip­ping Point” by Mal­colm Glad­well, there has been a fairly large body of research in this area but, for what may be the first time in his­tory, there is now a heavy trove of data that can be analyzed.

4. Prob­lem Solving

Sites like Google Answers are work­ing on pro­vid­ing bet­ter answers to ques­tions. Add-in some social net­work glue and one could be able to fig­ure whether the per­son is a sub­ject mat­ter expert in the area he/she is answer­ing the ques­tion about. For exam­ple, you might want to trust an indi­vid­ual with strong net­work ties in tech­nol­ogy on ques­tions related to tech­nol­ogy but might be a lit­tle more wary of answers that per­son would pro­vide about med­ical care (and sim­i­larly, you might trust a doc­tor more about med­ical care than you would a com­puter geek). Social net­works, when seen through the lens of exper­tise, can pro­vide quick access to answers from sub­ject mat­ter experts in one area. It is impos­si­ble to know every­thing but you might have a friend of a friend of a friend who has the answer in a spe­cific area you are researching.

Sim­i­larly, social net­works can pro­vide a way to get social mat­ter experts to con­nect and work col­lec­tively on dif­fi­cult prob­lems. When com­bined with digg–like fea­tures, social net­works could become a way to speed up the vet­ting process on sci­en­tific pub­li­ca­tions by allow­ing a large set of peers to review arti­cles and rank them accord­ing to value. This, in itself, could help human­ity make rad­i­cal moves for­ward in the area of sci­en­tific research.

Take, for exam­ple, my friends at ACOR who have been think­ing of devel­op­ing, in part­ner­ship with the National Can­cer Institute, a data-mining sys­tem that ana­lyzes infor­ma­tion about patients to iden­tify poten­tial root cause for dif­fer­ent can­cers. Here, we see social net­works (in this case, via mail­ing lists that are finely tar­geted) poten­tially being use­ful to help advance sci­ence and hope­fully dis­cover some root causes for can­cer. A set of tools to such gran­u­lar com­mu­nity could help a sci­en­tist, for exam­ple, sent a ques­tion­naire to a sub-segment of the pop­u­la­tion to test a hypoth­e­sis (eg. “let’s see if peo­ple who have skin can­cer and drank more than 1 glass of milk a day are react­ing bet­ter to this type of drug?”) before decid­ing to do a clin­i­cal trial. If a spe­cial­ized social net­work for such com­mu­nity was cre­ated, there might be no end to how much data could be gath­ered. Thing of it as a shot­gun approach to medicine.   

3. Mar­ket­ing

Mar­ket­ing, off course, is all about deep knowl­edge of the audi­ence. The best way to mar­ket a mes­sage is to dis­cover what moti­vates peo­ple and how to craft the mes­sage to match the moti­va­tions. When com­bined with the data­base of inten­tions, a social net­work can work as a set of focus groups for mes­sages. Test­ing dif­fer­ent mes­sages on a nar­row audi­ence can allow peo­ple to bet­ter mar­ket their products.

2. Rep­u­ta­tion Management

The old adage is that “it’s not what you know, it’s who you know“ is at the core of social net­work­ing. As more and more peo­ple are online and more and more inter­ac­tions are hap­pen­ing between peo­ple with weak ties, assess­ing a person’s rep­u­ta­tion is increas­ingly impor­tant. LinkedIn has keyed in on that effort by giv­ing peo­ple the abil­ity to “endorse” mem­bers of their social net­work, pro­vid­ing more infor­ma­tion about how a per­son per­formed in a par­tic­u­lar job. In a sim­i­lar fash­ion, pro­files no Ebay allow buy­ers and sell­ers to assess the track record of a buyer or seller before mak­ing a trans­ac­tion. Endorse­ments by one’s strong ties gen­er­ally reflects much higher than by some­one you don’t know. Thus, social net­works can work as the glue to rep­u­ta­tion man­age­ment. It is not enough for peo­ple to know that a per­son is seen as impor­tant by some ran­dom stranger but when one dis­cov­ers that their friends or col­leagues have endorsed a par­tic­u­lar indi­vid­ual, they tend to trust those opin­ions more heavily.

Let’s take a pedes­trian exam­ple: imag­ine you need to get some elec­tri­cal work done in your house but don’t know any elec­tri­cians. By look­ing at your social net­work, you could find such an expert with ease as the best elec­tri­cian might be linked to your friends. In a way, social net­works are just an exten­sion of ask­ing peo­ple for rec­om­men­da­tions. Which brings me to the last oppor­tu­nity on this list.

1. Rec­om­men­da­tion

Rec­om­men­da­tion is a very pow­er­ful dri­ver to deci­sion mak­ing: whether it is for hir­ing a per­son, pick­ing a new prod­uct, or find­ing a gen­eral direc­tion, humans tend to look to their exist­ing net­work and do a sub­con­scious “most-like” analy­sis of the infor­ma­tion they receive. For exam­ple, Ama­zon has been very suc­cess­ful with the “peo­ple who bought this also bought…” and “peo­ple who looked at this also looked at…” features. As they gather more data, pat­terns emerge.

Sim­i­lar approaches can be taken into the search space (where what peo­ple linked to or clicked on is ranked higher than other stuff) and in other areas like music (last.fm comes to mind) or other media con­sump­tion (for exam­ple, the suc­cess of aggre­ga­tor like Digg, tech­meme or tail­rank can be attrib­uted in large part to the need peo­ple have to know what other peo­ple think is good).

Con­clu­sion

Social Net­works should not really be a set of stand­alone tools but they are essen­tial to build­ing the next set of appli­ca­tions that lever­age the power of the crowds. As such, social net­work­ing should be a fea­ture and not an end-goal until itself. The com­pa­nies that under­stand this basic rule will be the ones that suc­ceed in that space, lever­ag­ing oppor­tu­ni­ties cre­ated by social net­works in a fash­ion that will pro­vide unprece­dented benefits.