Category Archives: trust

Nextdoor and NYC team up to enhance neighboring

Flickr/kiki99

Flickr/kiki99

I’ve written in the past about efforts to use 21st century technological tools to enhance neighbors’ connections with each other, the sort that are far less common today than in the 1960s or 1970s.

Nextdoor, a leader in this space, has partnered with NYC Mayor  Bloomberg to provide Nextdoor services in 1800 existing NYC neighborhoods.  It’s a win-win partnership.  The city gets a platform that enables them to pinpoint messages that need to get out to certain neighborhoods (such as upcoming events, programs, news, emergency bulletins), and NYC through NYCGov will let New Yorkers know how they can better connect with their neighbors through the Nextdoor platform.  (These Nextdoor networks are secure so users have to verify they actually live in a neighborhood to join and users get to control what of this information is public and what is shared privately between neighbors.)

Nextdoor makes it far easier to share information with neighbors (on mobile phones or computers), whether it is about a community issue, or finding a good painter or babysitter, or setting up a block party, or providing other advice or recommendations.  Nextdoor is also an example of what Bob Putnam and I call “alloy” social capital that combines virtual and face-to-face elements.  We believe that alloy connections are stronger than either the purely virtual social connections in an online gaming community (for instance) and also stronger than purely face-to-face connections.  The platform of Nextdoor also makes it more likely that one will meet new neighbors when one follows up on a e-post by inviting a neighbor to coffee, or start waving to or talking with a neighbor who one previously passed silently.  And for neighborly relations that already exist, Nextdoor can help strengthen them by increasing the frequency with which one connects with neighbors.

See earlier post about Nextdoor here.

The Nextdoor-NYC announcement, builds on similar announcements with 120 city governments over the last 12 months including cities like San Jose, Denver,  Dallas or San Diego.  New York City is an iconic city of 8.3 million people and this agreement offers the potential to unlock a lot of social capital so we’ll watch this with bated breath and hope that many other cities will follow NYC’s lead.

It will be interesting down the road to plot out the rise of Nextdoor usage by neighborhood with its impact on social capital measures (e.g., trust of neighbor or borrowing/lending from neighbors) and on putative downstream measures (such as lower crime rate, from the higher level of e-“eyes on the street” to transmute Jane Jacobs‘ pearl of wisdom into the digital age.

See earlier Social Capital blog post on Nextdoor.

See Wired story about this collaboaration of Nextdoor and NYC.

Nextdoor: e-neighborhood networks

 

Sarah Leary, Nextdoor.com

I had an interesting conversation with Sarah Leary, co-founder of Nextdoor.

Sarah comes from having worked at epinions (with the other Nextdoor co-founder Nirav Tolia) and discovering how one could capture reputation and trustworthiness online (in terms of ratings) and how people thirsted to compete with one another to be helpful in their comments.

Nextdoor is now trying to localize social networks.  [A bit more at the bottom of this earlier blog post.]

Nextdoor’s approach is as follows:

1. Individual social entrepreneurs can apply to launch Nextdoor in a community.

2. The social entrepreneur fills out an application form and if he/she looks like they are serious about this and well integrated in the neighborhoods, they are invited to proceed.

3. The social entrepreneur self-defines their community (using tools that make it easy to incorporate parcels, census blocks, etc.).  Ideally a community is between 50 and 200 households.  And they are not allowed to choose geography that is already part of another active Nextdoor community.  And the social entrepreneur invites his/her friends to join.

4. The Nextdoor community is in a pilot period for 21 days, and if there are not 10 active users by then, the site goes dark and users are told that the site hasn’t achieved sufficient momentum.

4. Anyone joining can see a map of the “neighborhood” and see which houses have or have not already joined. Those on the site have the power to invite others in their neighborhood to join the site (by e-mail, postcard, etc.).  A lot of their growth comes from strong word-of-mouth.

They launched in October 2011 and are already in 2100 communities nationwide.  Surprisingly, they have found that in order for sites to be viable, it is less important that they get to some percentage penetration of the community but to get to a surprisingly small number of active users.

All users are verified (by phone, by postcard, by address from a credit card, or by neighbor confirmation) that they are in the relevant neighborhood.

As one would expect from social capital theory, they find that people do in general behave surprisingly civilly.  [This because participants are highly likely to encounter each other off-line, and those behaving dishonestly are likely to be ostracized or  sanctioned.]

Their original motivation for starting the site was to get individuals involved in civic issues, but they found that much of what people wanted to do was discuss crime, or get recommendations, or find local people to sell something.  But their anecdotal experience is that these exchanges help forge the social networks that can be activated when civic issues arise.  Moreover, they believe that these transactions help reinforce generalized trust of participants in their neighbors.

We’ll look forward to hearing about their lessons and what works well or doesn’t.  Obviously, it would be great if they and others succeed in building stronger neighborhood engagement for all the reasons noted in Bowling Alone: better health, lower crime rates, better performing schools and governments, and happier residents.

It remains to be seen what lessons they learn about how online social connections can be maximally used to spur and reinforce face-to-face connections as well.

The how of social capital

Flickr/drjausSocial capital is a powerful resource for individuals and communities.  For individuals embedded in dense social networks, these networks and the attendant norms of trust and reciprocity strongly shape individuals’ ability to land jobs, earn higher salaries, and be happier and healthier.  But, even for those not in the networks, having neighbors who know and trust one another affords benefits in some domains:  better performing local government, safer streets, faster economic growth and better performing schools, among other public goods.

For sure social capital can be used toward negative ends: Al Qaeda, the Crips and the Bloods, the Michigan Militia are all examples where group members can accomplish things that they could not accomplish individually (because of  group social capital).  That said, the literature supports that the vast majority of what social capital is used for is to produce positive ends, not negative ones.

But why?  What makes social capital so powerful?

Robert Putnam and I had always focused on information-flows as the key mechanism.  So these social networks:

  • enable individuals to access valuable information: how to get something done, hear of  job leads, learn how better to promote one’s health, find out what is happening in a community, etc.; or
  • help individuals find partners for joint economic transactions (e.g., to know with whom to partner  in business, to close a sale to a friend or a friend of a friend, to locate a neighbor with whom one can exchange tools or expertise); or
  • spread reputations of members (or neighbors or local merchants) which causes all people in these networks to behave in a more trustworthy manner and facilitates altruism.  There is always a short-term gain to be had from cheating someone, but if the social networks quickly spread the information that one cannot be trusted, this short-term gain is swamped by the lost future opportunity to do business with others; thus it becomes more rational to be honest and trustworthy in communities (physical or otherwise) with strong social networks. Individuals are also likely to be kinder and more altruistic toward others because they know that “what goes around comes around” in densely inter-connected networks and communities; and
  • facilitate collective action: it is easier to mobilize others around some shared goal like politics or zoning or improving trash pick-up if others in the  community already know and  trust you, rather than your having to build those social relationships from scratch.

But Connected (by Nick Christakis and James Fowler) raises a different frame for thinking about this issue: network effects or contagion.  Are there properties of the networks themselves that help spread practices, independent of the flow of information?  This is difficult to answer fully since much of their evidence comes from the Framingham Heart Study where  they know who people’s friends are but not what they are doing with each other or what they are saying to each other.

That said, some of their results can be explained by information flows (e.g., political influence, or getting flu shots), but some seem likely to be working through other channels and not through information-flows (e.g., happiness or loneliness cascades).

In these “network effects” or contagion, Fowler & Christakis typically find that the strongest “network” effects are directly with one’s friends (one degree of separation), but these effects also ripple out two more levels to  friends of one’s friends (two degrees) and friends of the friends of one’s friends (three degrees).  As one would expect, much like a stone dropped in a pond, the ripples get smaller as one moves out.  In fact they refer to the “Three Degrees of Influence” Rule that effects are typically only seen up to three degrees out and not further: in the spread of happiness, political views, weight gain, obesity, and smoking.  For example, in happiness, if one is happy, one degree out (controlling for other factors), one’s friends are 15% happier, at 2 degrees of separation they are 10% happier, and they are 6% happier at 3 degrees of separation.  For obesity, the average obese American is more likely to have obese friends, one, two and three degrees of separation out, but not further.  Quitting smoking has diminishing effects out to three degrees.  For political influence, they note a “get-out-the-vote” experiment that shows that knocking on a stranger’s door and urging the resident to support a recycling initiative had a 10% impact on his/her likelihood to vote for the initiative; what was noteworthy to Christakis and Fowler is that the door-knocking made the spouse (who was not at the door) 6% more likely to support the recycling initiative based on communication with his/her spouse.  They conjecture that if this 60% social pass-through rate of political appeals (6% for spouse vs. 10% for person answering door) applied to one’s friends and if everyone had 2 friends, then one person urging friends to vote a certain way would have a 10% impact on one’s friends, a 6% impact on one’s friends’ friends (2 degrees) and a 3.6% impact 3 degrees out.  Multiplying these political effects all the way through, one vote could create a 30x multiplier. [The example is eye-opening and suggests that voting and political persuasion may be less irrational than thought, but also is based on a huge number of assumptions and assumes no cross-competing messages from friends.]

In an experiment on altrusim (explained in this post) Christakis & Fowler found that $1.00 of altruism, ultimately produced $1.05 of multiplier effect ($.20 one ripple out with 3 others and $.05 of altruism two ripples out with 9 others).

Christakis and Fowler, in their book, talk about contagion effects in voting, suicide, loneliness, depression, happiness, violence, STDs, number of sexual partners, binge drinking, back pain, and getting flu shots, among others.  [One summary of many of their findings, which they note, is "You make me sick!"]

Why do these effects only reach out 3 degrees of influence?  Christakis & Fowler suggest 4 potential explanations.

1) intrinsic decay: C&F liken this to a game of telephone where as the information gets repeated, the content gets lost, or the passion and knowledge of the initiator gets dissipated.

2) Instability of ties: because of what is known as “triadic closure“, if A is friends with B and B is friends with C, it is likely that A will become friends with C.  Because of this, closer-in ties between people have more routes connecting them, and further out ties are more dependent on only one pathway connecting them.  For example, assume Abby and Fran were friends 3 degrees removed via Bert and via Charles. If any of these intervening friendships end (say Bert is no longer friends with Charles), Abby loses her tie to Fran.  Thus, these outer ties are much less stable and averaged across all the “3 degrees of influence” friendships, many more may have zero effect because the path of influence dies out as friends change.

3) cross-information:  as one gets further out away from you, say the friends of the friends of your friends, all of these folks are getting lots of cross-stimuli from lots of other sources (many of which may come from different clusters with different habits or values) and these cross-stimuli start to cancel each other out.

4) evolutionary biology: C&F note that humans evolved in small groups that had a maximum of three degrees of separation so it may be that we became more attuned to being influenced by folks who were in a position to alter our gene pool.

So what are the network influences independent of communication.  There seem like 6 possible channels, and often it is hard to separate one from the other, although some may make more sense for the spread of behaviors and others may make more sense for spread of attitudes or emotions:

1) homophily: “Homophily” is the practice of befriending others like you — “birds of a feather flock together.” Being friends with people who are different than you can be stressful.  This is why in mates and in friends we are likely to choose others with whom we have a lot in common — think of arguments you’ve had with friends about where to go for dinner or what is right or wrong with the world when those friends have very different tastes or politics.  For this reason, one reason for increased clustering over time of obese people or smokers or binge drinkers is that it is stressful to be in groups where one is the minority and either constantly noodging others to change their behavior or else your finding yourself frequently doing what your friends want to and what you do not (e.g., eat fast food, smoke, or listen to heavy metal rock music).  As a consequence, people may vote with their feet and form new ties or strengthen ties with others with whom they have more in common.

2) norms/reference groups/culture/peer pressure:   we often measure the reasonableness of our behavior against our friends.  For example, if our teen friends have all had 6 sexual partners in the last year, then repartnering seems far more normal than if one is friends with a group that is heavily monogamous.  Ditto with obesity or smoking or other possible traits or behaviors.

3) subconscious/imitation:  as suggested with “emotion” below, sometimes we mirror others’ behavior or emotions without even thinking about it.  C&F say it makes sense to think of people as subsconsciously reacting to those around them without being aware of any larger pattern.  They talk about processes by which a “wave” at a sporting event takes place, or fish swim in unison, or geese fly in a V-formation, or crickets become synchronized — all of these happen by individuals mirroring those around them.  And in the process, emergent properties of the group arise (much like a cake takes on the taste unlike any of its individual ingredients).

4) emotions: C&F note that emotions actually affect our physical being — our voices, our faces, our posture.  In experiments, people actually “catch emotions”: others become happier by spending time around happy people or sadder by hanging out with depressed individuals.  In experiments, smiling waiters get bigger tips.  It seems quite plausible that cascades like loneliness, happiness, depression, etc. could spread simply from emotional states, independent of any information flowing through these friendships.

5) social invitations for shared action: friends often invite friends to do things — that’s part of friendship. For behaviors, one of the ways they can spread through networks is that, for example, thin friends could invite friends to exercise more, or obese friends could encourage friends to get ice cream together, or smokers could encourage others to leave the dance for a cig.

Connected notes that it is often hard, for example, to tell imitation and norms apart, “When a man gives up his motorcycle after getting hitched, is he copying his wife’s behavior (she doesn’t have a motorcycle) or adopting a new norm (the infernal things are unsafe?)”

Connected also notes how behaviors or attitudes can spread several social links out, even without the intervening link changing.  They suggest that Amy could have a friend Maria who has a friend Heather.  (Amy and Heather don’t know one another.)  Heather gains weight.  Maria, who really likes Heather, becomes less judgmental of her weight and gradually less judgmental of  obesity in general.  Maria doesn’t change her behavior but when Amy stops exercising with Maria, Maria is less likely to pressure her to resume.  Thus Heather’s obesity changes Amy via Maria (by Maria no longer urging her to keep exercising), but Maria doesn’t change her behavior and Amy and Heather don’t know one another.

It’s interesting stuff to ponder and makes one think more expansively about the role and mechanisms of social capital.  It also evokes a conversation with a Saguaro Seminar participant back in 1998 concerning whether black kids and white kids doing sidewalk painting together on the steps of an art museum could promote inter-racial trust, even if the black kids and white kids didn’t know each other, didn’t talk to one another and never met again.  [My hunch is yes, depending on the strength of their pre-existing beliefs about inter-racial trust, but that talking could make the exchange far more powerful.] Another Saguaro participant wondered whether singing together in a chorus helps build social capital, even if one never has a conversation directly with another member of the chorus.  (In the latter example, in addition to being highly unlikely, you are at least getting some non-verbal information over time from the other choral members about their trustworthiness: do they come regularly and on time, do they respectfully listen to and follow the choralmeister?)

I welcome your thoughts.

For more on the network effects, read pp. 24-30, 25-43 and 112-115 in Connected.

Using bicycle thefts as measurement of trust

(photo by Ned Lyttelton)

(photo by Ned Lyttelton)

Other experimenters have tested community-trustworthiness by dropping “lost wallets” in communities with a small amount of money and an ID card that says “If lost, please return to Mr. XXX  at YYY address.]  By dropping wallets randomly in different communities, they can measure the percentage of wallets returned intact (without the money missing).  It turns out that such empirical measures correlate strongly with the percent of neighborhood residents who report that others can be trusted.  [See also my earlier post on a related topic.]  So, it’s not just that in some communities people are drinking funny water….   One recent researcher (a bit less scientific) dropped those wallets and then videotaped those taking the wallets.

A idea from Mariano Pasik, a community advocate and publicist in Buenos Aires, Argentina is that community members should leave out bicycles and then film to see what percent of them are taken and over how short a period.  One can imagine that if people did this in communities across the world, one could use a mashup to present these data on an empirical measure of trust (although it is not always clear whether the thieves are community residents or outsiders).

TY to PSFK for a heads-up about this.

Trust/Approval of federal government hits all-time low

Flickr photo by reskiebak

Approval ratings for Congress dropped into single digits this month for the first time since CBS News and the New York Times began asking the question more than three decades ago.

A New York Times/CBS poll conducted between October 21-24, 2011 showed just 9% percent of US respondents approving of the job of Congressional lawmakers. [The question read "Do you approve or disapprove of the way Congress is handling its job?'] This is a drop from 11% back in September and the first time approval ratings have been in single digits over the almost three and half decades that the question has been asked (since 1977). [84% in the recent October poll said they did not trust congressional lawmakers and 9% said they didn't know.]

Rates of approval peaked in the early 2000s when over 60% approved of the way Congress was handling its job and has dropped precipitously since then.

The same precipitous drop is true about trust of national government.  [Question: "How much of the time do you think you can trust the government in Washington to do what is right?"]  Trust of national government hit an all-time low in October 2011 of 10%.  Back in the early 2000s, about 55% of Americans said they trusted the government in Washington.

One can see the time series for Congressional approval and trust of the federal government since 1977 here.

For sure, a heavy component in these declines in trust are macro assessments about the economy and the country.  That said, at least in the short-term, the precipitous decline in trust of government presents a strong headwind for those who aspire to mobilize government to do something either about record high levels of inequality or to help stimulate the US out of the deepest recession it has experienced in the last century.   I am also working on some scholarship with Chaeyoon Lim (not yet published) that suggests that partisanship may be greater in times of greater economic woes, so this may also be playing a role in the declining trust.

See earlier comments of Bob Putnam from 18 months ago on these declines in governmental trust.

Americans far less trusting than per capita wealth would predict

Catherine Rampell has a couple of interesting charts describing the relationship of trust, income and equality (among countries).

The US is 10th most trusting of the 30 countries examined (with 48.7% saying that others can generally be trusted).  Norway and Denmark are the most trying with almost 90% saying that others can be trusted; Turkey and Mexico are the least trusting with only 20-25% of residents saying that others can be trusted.

Since wealthy countries generally are more trusting, it’s surprising that America is only ranked 10th.


The U.S. is the country in the top center of the graph, way above the black regression line with median equivalized income of $27,000 per person (y-axis) but trust just below 50% (x-axis).  If one moved the US over to the right until it hit the regression line it would have social trust levels of 90%, like Norway.  [better picture here.]

The reason for America’s low level of trust can be seen by looking at the levels of inequality in the US.  More equal countries tend to have higher levels of trust, and viewed through this lens, Americans are just as trusting as one would expect, down around the levels of trust and inequality of a Portugal or a Poland, which while far poorer than the US has similar levels of equality to the US.

The implicit conclusion seems to be that income equality trumps wealth when it comes to trust, which makes some sense as it may engender a “we’re-all-in-this-together” esprit de corps.  But the regression line, if anything, seems to better fit countries for the graph of trust against income per person than the level of trust maps onto levels of equality.  And notably, Denmark and Norway, have higher levels of trust than one would expect from their level of equality.

Food for thought…

See NY Times Economix, “Trust Me, We’re Rich” (Catherine Rampell, 4/18/11)