Category Archives: social 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.

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.

Using evolution to improve neighborhoods: The Neighborhood Project

David Sloan Wilson is undertaking an interesting project to try to learn the rules for evolving cooperation while improving his community (Binghamton, NY), a city of 47,000 in upstate New York that has fallen on hard times with the industrial flight of corporate mainstays. A March 2011 Gallup poll found Binghamton to be one of the five least liked cities in the US.  His effort is change all that is called the Binghamton Neighborhood Project (BNP).  It raises all the usual interesting questions about being dispassionate and objective in one’s research, and not attempting to alter the very metrics one is measuring.

BNP has done interesting mapping work (relevant to those of you that are interested in doing the same thing in your areas). For example, students dropped lost letters in different parts of the community and measured the percentage that reached their destination.  They charted the density of Halloween and Christmas decorations as an indicator of community pride, participation, and goodwill.  And they mapped their data in interesting ways, using krig maps to show pro-social peaks as well, peaks.  [See: Wilson, D. S., O’Brien, D. T., & Sesma, A. (2009). Human Prosociality from an Evolutionary Perspective: Variation and Correlations on a City-wide Scale. Evolution and Human Behavior, 30: 190-200.]  [See great sample of 3-D visualization of crime data for San Francisco here.]

Efforts include: a design your own park effort, a Regents Academy for at-risk youth where students are incentivized for good behavior and cooperation, the Binghamton Religion and Spirituality Project to survey and map Binghamton’s religious diversity.

The Design Your Own Park initiative seeks to transform abandoned lots into community playgrounds. Groups submit ideas and the community votes on the idea the most like.  The United Way of Broom County helps secure funding for the transformation and community groups agree to maintain the park.  The goal is to foster parks throughout the city and there are 5 park projects underway including a BMX bike park and a dog park.

At Binghamton’s Regents Academy, a higher percentage of at-risk students took and passed state tests than in other Binghamton schools, but no formal assessment has been done of the school.  Moreover, at least as of June, the regime of rewards was still changing weekly and the principal, Miriam Purdy, while believing in the importance of the incentives, did not believe that the incentive program is about evolution.

The Religion and Spirituality Project is motivated by Wilson’s belief that religion can play a central role in producing community cohesion and giving residents a sense of life meaning.

Wilson believes that community residents (using his biological training) can behave either like water striders (which pursue their goals single mindedly, ignoring others) or wasps (which work together subconsciously for their collective good).  Pro-social groups can outcompete those lacking social cohesion, so he believes there is an evolutionary element to encouraging prosocial behavior.  He believes the seven key elements to more effective collective efforts are: 1) a strong sense of group identity; 2) proportional costs and benefits for all residents; 3) consensus decision-making; 4) monitoring those who are anti-social; 5) providing graduated sanctions (ranging from minor slaps on the wrist to more serious sanctions for chronic infringers); 6) fast, fair conflict resolution system; and 7) autonomy/authority, nested within polycentric governance (which links these localized efforts together).  Above and beyond these factors, he believes that residents need lots of practice at cooperating, and often our affluence buys us out of community, in the same way that David Brooks refers to the Haimish line.

Listen to NPR story ‘Can Evolution Breed Better Communities?

Interesting Nature story (9 June 2011) on this called “Darwin’s City

Read “The Neighborhood Project: Using Evolution to Improve My City, One Block at a Time”; excerpt available here.

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)

Social trust important to social and political stability

Flickr photo by sp8254-catchingup

A new paper by Ken Newton and Sonja Zmerli called “Three forms of trust and their association” finds, counter to the assertions of Eric Uslaner or others, that social trust is important to modern democracies and is positively associated with other types of particular trust.

From seven questions relating to trust, factor analysis revealed two dimensions, one largely related to generalized social trust (the canonical, “Generally speaking, would you say that most people can be trusted or that you can’t be too careful in dealing with people,” and three other trust questions: trust in 0people one meets for the first time, trust in people of other religions and trust in people of other nationalities.  The second dimension that emerged related to particularized trust, covering questions like trust in family and people whom one knows personally.  Some variables like trust in neighbors loaded positively but less strongly on both the “generalized” and “particularized” factors.

The measure of political trust employed an index composed of 6 measures of confidence in political organizations like parliament, government, political parties, justice system, civil service, and police).

The paper uses World Values Survey (WVS) data from 2005-2007, choosing the 22 countries with the highest democratic scores on the Polity IV variable (New Zealand, Australia, India, US, Sweden, Finland, Great Britain, The Netherlands, France, Spain, Germany, Italy, Switzerland, Poland, Romania, Bulgaria, Slovenia, Cyprus, South Africa, Mexico, Peru, Chile).

High political trust is positively related to high generalized trust and political trust even exceeds levels of generalized trust in half of the WVS countries examined: South Africa, Switzerland, Spain, Finland, Slovenia, Italy, Cyprus, Germany, Chile, Mexico and India.

Their results best fit the “conditional” model of trust, namely that there is no incompatibility of generalized social trust and particular trust, but instead that particular social trust tends to form a conducive environment in which both general social trust and political trust can develop.

Newton and Zmerli’s analysis also contravenes a notion that people either trust or don’t based on their personalities; they find instead that individuals “choose whom and what to trust and combine varying degrees of trust or distrust in different objects.”

Finally, their results support what social capital would expect about the importance of generalized social trust on political well-workings and find something of a positive tipping phenomenon — what they call a “rainmaker” effect — that high aggregate levels of trust in society help influence individual trust levels.  [This “rainmaker” effect is less persuasive for me, since unless I’m misreading something, this is not panel data.]

See: “Three Forms of Trust and Their Association” (European Political Science Review 2011)