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Home - posts tagged as Tribes

Definition of an AOL searcher posted on February 6, 2010

Tribes

The users of different search engines fall into different tribes, according to this study in Ad Age. (ex Unbound Edition) That shouldn't come as a surprise. I found the definition of the AOL searcher especially poignant:
AOL customers feel less intellectual than their peers, are 55 and older, spend their money more responsibly, want to blend in to the crowd, feel like they've gotten a raw deal out of life, expect less from their future and, believe it or not, still use dial-up modems.
Hmmm. What sort of marketing campaign should we work up for them?
Incidentally, if any of you speak German, here's an article I wrote for the Frankfurter Allgemeine Zeitung. It's about what we should be storing in our heads, a theme I've been exploring a bit in recent talks.
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X-box Live: Where does it fit into "friends" series? posted on April 25, 2009

Tribes

Talked the other day with Marc Whitten, general manager of Microsoft's
Xbox division. This was for my BusinessWeek reporting on Friendship.
Xbox seemed relevant, because 20 million people play on the live
version, most of them searching, meeting, and playing with friends of
one type or another.
There are two approaches to friend-finding on Xbox. One is to find
people all over the world to compete with. That was the initial focus,
Whitten says. But his team has learned that a larger and richer market
features people who just want to hang out with friends they already
have. They may be down the block or across an ocean from each other.
In these meetings, the players often have unequal skills. This
has led to a growth in non-competitve games. People play on the same team. Whitten does this with his brother in Oklahoma. Otherwise, he says, he'd blow him away. After all, the guy lives Xbox.
I was hoping to learn that Microsoft was crunching all the Xbox Live conversation and friending data to find out about hierarchies and networks of friends. That's not the focus, though. They're less interested in learning about people than simply helping them find and play with their friends.
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danah boyd on Friendship posted on April 12, 2009

Tribes


This is a little film clip I did with danah boyd, a Microsoft researcher. She talks about decoding the patterns of our friendships. (If I were a pro, I would have edited out the first couple of seconds before she realizes the camera's running. But, actually, that moment of recognition, when she snaps into a smile, is my favorite moment in the whole clip. Not that you shouldn't watch the rest...)
This is part of the Friendship series I'm working on at BusinessWeek. I'm heading out to the West Coast tomorrow, and hope to talk to people at Facebook, LinkedIn, and elsewhere. I'll take along my flip camera and post more video, too.
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Locaccino: Tracking location with privacy posted on March 2, 2009

Tribes

Locaccino is a new location-based friend-finding service for Facebook. It comes out of Carnegie Mellon University, and the emphasis is on customizable privacy settings.
From the Web page:
Our technology allows you to easily define the times when you want
to share your locations. Locaccino lets you create groups for your
friends to simplify your location preferences. With Locaccino, allowing
your co-workers to see your location from 8AM – 5PM is a snap.
Locaccino
also allows you to specify where you can be located. Using a Google
maps interface, you can define regions where you do and don’t want
other people to be able to find you.
We'll see if Google adds these features to its Latitude application (which I have on my Blackberry). Of course, part of the fun is seeing what my colleagues are up to over the weekend. But we all should have the right to draw the curtain when we want. (If my editor looks on his Blackberry today, he'll see my dot blinking in snowy Montclair. Why suffer two monster commutes to New York just to write? At least that's my excuse.)
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| The view from my front window
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Microsoft search puts us in groups posted on January 30, 2009

Tribes

| Search has hit a plateau, according to Microsoft researchers. Figuring out the most relevant Web page based solely on the search query isn't advancing much beyond the state-of-the-art established in the last decade by Google. (And common wisdom is that Microsoft and Yahoo have caught up in quality, if not speed.)
Now Microsoft researchers, according to this story in MIT Technology Review, are attempting to group Internet searchers with others who have similar patterns. The idea is that we search for the same things as members of our behavioral tribe, and that with this added analysis, the search engines will deliver more relevant results. (They're going to present their study at a search gathering in Barcelona next month.)
One challenge will be gathering the data. For their study, researchers used a group of 100 colleagues who had agreed to participate. More details:
The researchers grouped people using explicit factors, such as their age, gender, participation in certain mailing lists, and job function. In some cases, implicit groups--such as people who appeared to be conducting the same task or appeared to have the same interest--were inferred. The researchers acknowledged that gathering such data in the real world could be tricky. But it could perhaps be collected through registration, by caching previous searches or by tapping into social-networking software.
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How the Numerati helped win it for Obama posted on January 24, 2009

Tribes

An essay I wrote:
News Analysis
January 23, 2009, 6:35PM EST
What Data Crunchers Did for Obama
Sophisticated political microtargeting efforts are grouping us in
surprising ways. For Obama, swing voters known as Barn Raisers proved
pivotal
By
Stephen Baker
About three minutes into his speech on Jan. 20, President Barack Obama spoke a word never before uttered in a Presidential inauguration speech:
"data.". The word may sound nerdy, and Obama used it in reference to
indicators of economic and other crises. But it's no coincidence the
word found its way into his remarks. The harnessing of data has been
crucial to Obama's rise to power.
Throughout the campaign, Obama and his team not only bested his Democratic and Republican rivals
in social networking and fund-raising through the Internet, they also
engaged in a data battle to locate potential swing voters. These
efforts zeroed in on hotly contested states and congressional
districts, where the shift of 1,000 or 2,000 voters could prove
decisive—meaning the focus was on only a tiny fraction of the voting
public. But to find those swing voters, both sides hired tech wizards
to sift through mountains of consumer and demographic details. They
scrutinized nearly everyone they could find.
Ten "Tribes"
One Democratic consultancy, Spotlight Analysis, took this hunt to
extraordinary lengths. Working on behalf of Democratic candidates,
though not directly for the Obama campaign, Spotlight crunched
neighborhood details, family sizes, and purchasing behavior. It then
grouped nearly every American of voting age—175 million of us—into 10
"values" tribes. Fellow tribe members may not share the same race or
religion, or fall into the same income bracket, but they have common
feelings about issues that transcend politics: God, community,
responsibility, and opportunity. Spotlight believes that one of these
tribes, a morally guided (but not necessarily religious) grouping of
some 14 million voters—dubbed "Barn Raisers"—held the key to the
contest between Obama and his Republican challenger, Arizona Senator
John McCain.
The definition of a Barn Raiser cuts straight to the heart of what
distinguishes political microtargeting from traditional political
groupings. Barn Raisers can be of any race, religion, or ethnic group.
About 40% of Barn Raisers are Democrats, or lean that way, and 27%
favor Republicans—though the group strongly supported President Bush in
his 2004 reelection campaign. Barn Raisers are slightly less likely to
have a college education than Spotlight's other swing groups. They're
active in community organizations but are ambivalent about government.
And they care more deeply than most people about "playing by the rules"
and "keeping promises," to use Spotlight's definitions.
With special appeals to Barn Raisers in swing states, Spotlight's
clients, including the Service Employees International Union and the
Democratic Senatorial Campaign Committee, hoped to turn battleground
states such as Florida, North Carolina, Virginia, and Ohio. The
data-based techniques they put to use, similar to those used to target
supermarket shoppers and even to hunt for terrorists, are turning
politics into the sophisticated calculations typically associated with
Google (GOOG)
and its ilk. In a fraction of a second, computers sort us into segments
and then calculate the potential that each of us has to swing from red
or purple to blue. For many, this signals the dehumanization of
politics.
Others say political data mining helps better pinpoint individuals
whose views and priorities may otherwise be overlooked. Consider a
voter in, say, Richmond, Va. Republican and Democratic data miners
count the number of children she has in school, they take note of her
car, her Zip Code, her magazine subscriptions, and the balance on her
mortgage. They might even find in her data that she has two cats and no
dog. (Cat owners lean slightly for Democrats, dog owners trend
Republican.) In the end, they place her into a political tribe and draw
conclusions about the issues that matter to her. Is that so horrible?
Behavioral Grouping
For generations, politicians lacked the means to study us as
individuals. So they placed us into enormous groups—blacks, Jews, gays,
union members, hunters, soccer moms—and treated us as masses. While the
rich and well-connected got to collar candidates at $1,000-a-plate
dinners, the rest of us were processed as herds.
Nowadays, Spotlight and other microtargeters (for both parties)
continue to place us into big groups. But the divisions are based more
on our behavior and choices, and less on the names, colors, and clans
that marked us from birth.
Spotlight embarked on its research three years ago by interviewing
thousands of voters the old-fashioned way. At first, Barn Raisers
didn't seem especially noteworthy. The group represented about 9% of
the electorate. It spanned genders, races, and religions.
But when Spotlight's analysts dug deeper, they discovered that Barn
Raisers stood at the epicenter of America's political swing. In 2004,
90% of them voted for President Bush, but then the group's political
leanings shifted, with 64% of them saying they voted for Democrats in
the 2006 election. Spotlight surveys showed that political scandals,
tax-funded boondoggles like Alaska's Bridge to Nowhere, and the botched
job on Hurricane Katrina sent them packing.
Suddenly, Spotlight had a line on millions of swing voters. The
challenge then was to locate groups of them in swing states. For this,
the company analyzed the demographics and buying patterns of the Barn
Raisers they surveyed personally. Then it instructed its computers to
scour commercially available databases for others with matching
profiles. By Spotlight's count, this approach nailed Barn Raisers three
times out of four. So Democrats could bet that at least three-quarters
of them would be likely to welcome an appeal stressing honesty and fair
play.
Still Swing Voters
Did it work? Spotlight hasn't yet carried out the surveys to
determine how many of its Barn Raisers backed Obama. But it's
reasonable to presume that amid that sea of humanity stretched out
before Obama on Washington's Mall on Jan. 20, at least some of those
were moved by microtargeted appeals. And if Obama and his team fail to
honor their mathematically honed vows, the Barn Raisers may abandon
them in droves. They're swing voters, after all.
And if there is one thing the research has made clear, it's this:
Even if Barn Raisers exist as a tribe only in a database, they take
broken promises very seriously. And they probably won't object if
data-mining politicians figure that out.
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How friends' friends can affect moods posted on January 3, 2009

Tribes

One of my Twitter buddies sent me the link to this New Scientist story on how things like happiness work their way through social networks. It's not just your friend's happiness that influences you, but also your friends' friends. So if you're unhappy, or thinking about taking up smoking, or even concerned that your child might be diagnosed with autism, look around and see what your friends' friends are up to.
Researchers are going to benefit from lots of new data about our social connections in the next decade or so. Facebook and MySpace are gold mines, of course. But there are also companies such as Sense Networks that are starting to track our physical movements, and to sort us into new behavioral tribes.
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Not really a social network or a web. It's just a leaf I found last summer. But you get the idea...
Soon, researchers like those mentioned in the article will be able to study the contagion patterns of obesity,
happiness, suicide, political philosophy. And of course the government
will be especially keen to understand the migration across social
networks of terrorist sympathies.
When I was researching The Numerati, I talked to scientists at the Naval Postgraduate School
in Monterey, Calif., who are attempting to model the diffusion of
certain ideas in places like Iraq. (Or, more specifically, in Iraq.)
Let's say the United States does something good in a town, like
building a medical clinic. How does positive news spread to other
towns? When I was there, the studies were based on simulations using agent-based modeling. In the future, they'll be able to replace many of these simulations with reality: our behavior.
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Modeling the cheating husband posted on November 26, 2008

Tribes

I swear I was working (on this Thanksgiving eve) when I came across this Cosmopolitan article on how to spot the cheating husband. It caught my attention because the instruction form a primitive version of a predictive mathematical model. In a sense, this model of a (potentially) cheating husband resembles the models Fair Isaac builds of people likely to default on mortgages.
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The Private Life of San Juan (1934)
And, suffice to say, both models, Fair Isaac's and Cosmos, can be wrong.
While Fair Isaac studies how many credit cards we have and how we juggle financial obligations, Somos focuses on different variables:
Was he spoiled as a kid?
Do his parents tend to baby him and help him out of financial jams?
Has he ever bragged about cheating on an exam or paying someone to write a paper for him in college?
Does he work mostly with women?
Is
he always logging in late hours, whether it be at the office, at dinner
with clients or on business trips?
Does he make a lot of money?
Can he talk his way out of anything (parking tickets, rolling into work late)?
Does he make an effort to charm everyone -- your coworkers, your older sister, a saleswoman?
When you go to parties, does he insist on making the rounds?
Does
he usually hang out with a crew of mostly single guys?
Do his friends encourage him to join them in just-for-men activities?
Do his pals have problems staying in relationships?
If the Numerati were to delve into this type of data, of course, they'd have to come up with a weighting for each variable. They'd build the model from a population including known cheaters, and then test it on others. Somehow I doubt Cosmo goes to such lengths.
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Found my grocery store bucket (or one of them) posted on October 21, 2008

Tribes

This data mining post declares that the oft-cited correlation between beer- and diapers-buyers is an urban legend. But they do unearth grocery data indicating that there one bucket of people who buy cat food, chocolate and red wine.
Hey, I thought: That's us! But the researchers clearly didn't get their data from New Jersey, because we buy our chocolate and cat food in one store and then have to go to another to buy wine (of any color).
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How to battle shopping barnacles posted on October 21, 2008

Tribes

Barnacles. They're the shoppers who look for bargain deals and try never to buy anything at full price. Many retailers want to locate these people and "fire" them. How to do that? For starts, they can stop spending money to send them catalogs.
On MineThatData, Kevin Hillstrom offers 43 tips, including many to deal with pesky barnacles. Here are three:
Returns:
Customers who return at least sixty percent of the merchandise they
purchased are likely to return merchandise in the future. If you're
looking to trim marketing expense, here's a place to do so without
negatively impacting profitability. (ie. don't send them catalogs)
Fulfillment:
Customers who failed to receive items in their last order are often
less likely to order in the future than are customers who receive what
they wanted to purchase. (ie. drop them)
Channel:
Customers who order from catalogs over the telephone "age slowly",
meaning these customers can be profitably targeted for a long time.
Customers who order online age faster, meaning that after "x" months
they become unresponsive. Customers who order via stores age very fast,
becoming unresponsive soon after a purchase.
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Cog psych yesterdy at Penn St. Try counting things w/out moving finger. You rock, nod, or tap foot,anything to create rhythm.

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The Book Bag - Zoe Page

The Wall Street Journal - John Derbyshire

Frankfurter Allgemeine Zeitung - Milos Vec

The Guardian (UK) - Steven Poole & Christopher Exeter

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