Google Is Distorting The Google+ Numbers

When asked, Google executives say Google+ has 50M sign ups, and 100M active users over a 30 day period. But they are stretching things a bit, to be generous:

Nick Bilton via NY Times

Although these numbers sound impressive, the catch is that Google Plus-enhanced properties include YouTube, the Android Marketplace and Google.com, the company’s flagship search engine. Yet Google contends that these numbers illustrate that more than 100 million people have signed up for a Google Plus account and are now actively engaging with Google Plus-related products across the company.

In a view from outside the company, a report released last month by ComScore, the market research firm, says Google Plus users spend about three minutes a month on the social network. By comparison, ComScore says that people spend an average 405 minutes a month on Facebook, the service Google Plus is trying to displace.

Google may be trying to plusify all of its properties, but unless people start acting like there is a real, deep, rich social experience in there, it’s just not going to displace anything.

If there was one lesson I’ve learned in the last three years working for [Secretary Clinton] and being witness to significant shifts in power around the world, it’s that there is a significant shift in geopolitical power globally right now, from hierarchies, like the nation-state, to individuals and networks of individuals. This is something that’s being accelerated by increasingly powerful and ubiquitous information networks.

Alec J. Ross at Davos as reported by The New Yorker (via cacioppo)

Relative to the social business movement: businesses have to exist in a world that is increasingly liquid, increasingly based on the shifting relationships in social networks, rather than more solid and fixed ties between hierarchical power structures, like nation states and global corporations. I am not making the ‘adapt or die’ argument, but one that is more compelling: business people are not stupid, and they will adopt tools and techniques that allow them to accomplish their aims more economically and efficiently. Social networks are displacing hierarchies not because they are more egalitarian, but because they increase social density, which is the root of innovation, serendipity, and the likelihood of new connections. They foster a richer human experience, and the possibility of a better way to live and work.

And in the geopolitical context, social networks represent an opportunity for a new approach to world affairs, one that has been largely unanticipated.

morganmissen: Caterina Fake cited this timeline to 50M users on why the worst thing a social network can do is force growth. “My perspective is it takes a while to grow this stuff,” she said to Liz Gannes in AllThingsD. “It takes time for the culture to grow. You need time to develop antibodies to spammers and trolls.” Adding user registrations at such a fast pace doesn’t leave enough time for a dedicated, engaged user community to organically create itself and establish norms, she argued.
Zoom

morganmissen:

Caterina Fake cited this timeline to 50M users on why the worst thing a social network can do is force growth. “My perspective is it takes a while to grow this stuff,” she said to Liz Gannes in AllThingsD. “It takes time for the culture to grow. You need time to develop antibodies to spammers and trolls.” Adding user registrations at such a fast pace doesn’t leave enough time for a dedicated, engaged user community to organically create itself and establish norms, she argued.

(Source: morganmissen)

Privacy Management On Social Media Sites by Mary Madden via Pew Social network users are becoming more active in pruning and managing their accounts. Women and younger users tend to unfriend more than others. About two-thirds of internet users use social networking sites (SNS) and all the major metrics for profile management are up, compared to 2009: 63% of them have deleted people from their “friends” lists, up from 56% in 2009; 44% have deleted comments made by others on their profile; and 37% have removed their names from photos that were tagged to identify them. How to read the ‘unfriending’ trend? One option: This rise in unfriending might not be about friendship, per se. People might be just throttling back the torrent of information that they are receiving in their social streams: stream overload. But the deleting of comments and removing name tags from photos would represent very different, and possibly more privacy-oriented motivations. However, if I delete a comment because someone writes something offensive, is that a privacy issue? Or is it a more of a cultivated image being publicly displayed? That would make it a publicy issue. I think we will have to get a lot more fine-grained in determining causality in these cases, and more attuned to the publicy/Goffman angle: the presentation of self in everyday online life.
Zoom

Privacy Management On Social Media Sites by Mary Madden via Pew

Social network users are becoming more active in pruning and managing their accounts. Women and younger users tend to unfriend more than others.

About two-thirds of internet users use social networking sites (SNS) and all the major metrics for profile management are up, compared to 2009: 63% of them have deleted people from their “friends” lists, up from 56% in 2009; 44% have deleted comments made by others on their profile; and 37% have removed their names from photos that were tagged to identify them.

How to read the ‘unfriending’ trend?

One option: This rise in unfriending might not be about friendship, per se. People might be just throttling back the torrent of information that they are receiving in their social streams: stream overload.

But the deleting of comments and removing name tags from photos would represent very different, and possibly more privacy-oriented motivations. However, if I delete a comment because someone writes something offensive, is that a privacy issue? Or is it a more of a cultivated image being publicly displayed? That would make it a publicy issue.

I think we will have to get a lot more fine-grained in determining causality in these cases, and more attuned to the publicy/Goffman angle: the presentation of self in everyday online life.

The Point Of Social Leverage Is Mobile?

I see that my old friend, Keith Teare, has written a guest post at Techcrunch, making the case that Facebook and Google have inherent ‘structural’ problems in the way they manage information sharing which have become starkly apparent with Google’s new privacy policy and Facebook’s endless privacy issues.

Keith Teare, Google, Facebook, Privacy — And You

There is a big structural problem for both Google and Facebook as they contemplate the product consequences of consumer reactions to their product roadmap. In a centralized platform it is incredibly hard to create easy-to-understand controls that give each user the ability to control, at a granular level, what they share and who with. Grand policy shifts, like that which came out of F8 and which we are now seeing from Google, tend to assume all users are the same and will want the same thing.

In reality, users are more complex. I might want to save a private video to a personal storage space one moment, share something with a select group of friends another moment, and broadcast something to the world five minutes later. The web services infrastructure that both Facebook and Google are based on does not easily permit such fine grained control for users without also imposing serious effort. As we all know, that leads users to stick with the default settings most of the time.

So, despite good intent by the teams at both companies, one-size-fits-all decisions are the norm.

Mobile to the rescue?

Structural problems usually require structural solutions. What it seems consumers are asking for is a world in which we all know what we are sharing and who with — but where we don’t have to do a huge amount of work to achieve that. Google Circles seems to be a nod in this direction as are Facebook’s groups. But neither is really easy enough or sufficiently integrated into the flow of the products to really solve the problem. Both require a huge management overhead.

As I argued earlier this week in “Google, Look Out Behind You!“, the spread of smartphones may be part of the solution here. Hundreds of millions of consumers are now carrying around connected still and video cameras with lists of contacts in the address book, often already organized into meaningful groups. Decentralized decision-making is very easy when there are decentralized software clients under the unique control of each user. The ability to be private one moment, selectively share the next and then publicly broadcast a few minutes later is easy to achieve in this decentralized software architecture. And service providers can never become bad actors — simply because they do not own our information or the full social graph. The cloud becomes a means of delivering messages to the phones and the place where we store our media. But it’s not the place we need to trust to make decisions about what gets shared and who with.

So, Keith broadly paints a picture — users being forced into an oversimplified social architecture by Google and Facebook in which groups (or circles, which are a slightly different take on groups) are the mechanism of sharing — and hints that the problem is intractable for web-based social tools.

The answer is smartphones, he suggests: our personal devices, which we already use in myriad ways to connect with and share with others. He must believe — without saying so explicitly — that the solution lies in observing what we share and with who on our smartphones, and to refine that natural body of information into a bottom-up determination of who’s who in our world.

Imagine a Venn diagram of dozens — or hundreds — of sets of friends, where any friend could be in zero to all the sets, and all the sets are constantly in flux. And without us having to create all the scaffolding for it to work.

Obviously, Teare is not content to wave his hand at this: he’s started a company to actually build the solution:

Keith Teare, Seed and Series A Funding

just.me is a new architecture built on top of the mobile, and particularly the smartphone, ecosystem. It doesn’t take the web as its starting point, it takes the highly personal and ever-present mobile Internet as its starting point. As such it is focused on defining a new consumer software experience, not replacing an existing one. It is also focused on the freedom that comes from placing social tools on a device the consumer fully controls, and not building a big cloud service that owns or acts on the consumers data. We don’t know all of the questions this gives rise to yet, never mind all of the answers. But we are really excited about building on this new ecosystem and learning with users as we go.

I’ve been suggesting that the next wave for social networks is the social operating system — where exactly the problems that Teare is talking about are solved by building social primitives into the foundation of our online experience — but Teare is pushing at a transitional step, based on the mobile device as the logical point of leverage in the transition to the next generation of social tools.

Harvard researchers underwhelmed by peer influence on Facebook - Bob Brown via NetworkWorld

Harvard researchers Kevin Lewis, Marco Gonzalez and Jason Kaufman published a paper called Social selection and peer influence in an online social network, and it seems to suggest that peers have a smaller influence on what we like than people may think:

Bob Brown via NetworkWorld

Using the Facebook data from a group of more than a thousand college students at one college, the researchers found that students whose music and movie tastes were similar were more likely to become friends or influence the formation of new friends, though book tastes were less of a factor in either case (maybe it would be different for older people, once the book club years kick in?).  The fact that music and movies tend to be more social activities probably has a bearing on their influence on friendships, the researchers write.  They found tastes in classical and jazz music were more likely to get passed along through friendships than tastes in indie/alternative music, where the aficionado of such music might be the sort to be the token indie/alt music lover in a group.

Devin Coldewey doesn’t buy this at all:

[…] the study is also clearly flawed in ways that those versed in social graphs are likely to easily perceive. Pulling useful data from social networks is like catching lightning in a bottle, and I wonder whether the findings may in fact be, as the study attempts to avoid, “a spurious consequence of alternative social processes.”

The central source of data for the study, in fact, doesn’t strike me as solid. Tracking the interests of college kids is a sketchy endeavor in and of itself, but tracking it via their Facebook favorites (i.e. what shows on your profile, not what you post about or share) seems unreliable.

After all, not only does everyone use the network in their own way, but the network itself has changed. Putting Wilco in your favorites is a different act from liking Wilco’s Facebook page, their official band site, or posting their latest video. Gauging someone’s interest in a movie or band by the favorites factor alone is inadequate. Their findings are essentially that taste doesn’t diffuse the way you might expect. But while the data support this, nothing supports the data.

Flattening huge sets of data and removing potentially conflative or distracting connections (“disentangling,” to use the researchers’ well-chosen word) is the bane of social research, and with a limited window on a huge field of data, like that these researchers had, it’s especially hard.

Who among these people was a supernode? What were their Twitter counts? What was the most common unit of interest? How many total posts, how many total favorite changes, how many total friends? The process of disentanglement only gets harder and harder, and the amount of indispensable data grows. The researchers have used advanced statistical techniques, but the data they were interpreting doesn’t seem to be at all complete.

The study does establish something that I think we perhaps understand is true already: you befriend people because of your overlaps in taste, but it’s rare that your existing friends change the tastes you already have. This is as much true out in the “real” world as it is online.

Coldewey is a bit off kilter with his general pronouncements about the difficulty of pulling factual information from social netwroks: they have been shown in many studies, for decades, to be immensely important predictors of health, happiness, trust, and a long list of other factors.

Still, I have to agree that since the results are so counterintuitive, it might be important to segregate friends from influencers. My hunch is that influence follows the power laws, and so unless you find the people that have super levels of influence — and see what strange gravity disturbances they cause — you might not think that there is anything going on at all.

(Source: underpaidgenius)

Some Degree Of Separation

The six degrees of separation meme has surfaced again, based on new research from Facebook — in collaboration with researchers at the Università degli Studi di Milano — that suggests the average path length from one Facebook user to another has fallen to 4.74, and has been shrinking as Facebook has grown larger.

The N degrees of separation idea was first suggested in a short story by the Hungarian author Frigyes Karinthy:

Stowe Boyd, Everything is Different

In Albert-László Barabási’s Linked, the author explains that the origin of the “six degrees of separation” notion that underlies all social networking theory was the brain child of a Hungarian writer, Frigyes Karinthy. In 1929, Karinthy published his forty-sixth book, a collection of short stories entitled Everything Is Different (Minden masképpen van), which is now out of print and apparently lost to us.

Albert-László Barabási, from Linked

The short story collection was a critical failure and soon sank into obscurity. It has been out of print ever since. […] But there is one story, entitled “Lánceszemek,” or “Chains,” that deserves our attention.

“To demonstrate that people on Earth today are much closer than ever, a member of the group suggested a test. He offered a bet that we could name any person among earth’s one and a half billion inhabitants and through at most five acquaintances, one of which he knew personally, he could link to the chosen one,” writes Karinthy in “Lánceszemek.” And indeed, Karinthy’s fictionaly character immediately links a Nobel prizewinner to himself, noting that the Nobelist must know King Gustav, the Swedish monarch who hands out the Nobel prize, who is in turn a consummate tennis player and plays occasionally with a tennis champion who happens to be a good friend of Karinthy’s character. Remarking that linking to celebrities is easy, Karinthy’s character demands a more difficult assignment. Next he tries to link a worker in Ford’s factory to himself: “The worker knows the manager in the shop, who knows Ford; Ford is on friendly terms with the general director of Hearst Publications, who last year became friends with Árpád Pásztor, someone I not only know, but is to the best of my knowledge a good friend of mine — so I could easily ask him to send a telegram to the general director telling Ford that he should talk to the manager and have the worker in the shop quickly hammer together a car for me, as I happen to need one.” Though these short stories have been neglected, Karinthy’s 1929 insight that people are linked by at most five links was the first published appearance of the concept we know today as “six degrees of separation.”

And Now, Everything Is Different

The “six degrees” meme was rediscovered decades later by Stanley Milgram, who engendered an entire branch of science through his groundbreaking investigations into social networking. His initial foray into the field nearly confirmed Karinthy’s magic number five. Milgram’s research was astonishingly similar to Karinthy’s Ford example — getting random people in various Midwestern cities to pass along a letter through their personal contacts, heading toward one of two Massachusetts residents. And after all was said and done, the average number of hand-offs in the successful cases turned out to be 5.5; rounded up, this is the core for the “six degrees of separation” concept.

Another few generations have passed since Milgram’s 1967 experiment, and the principles of social networks have entered the popular mindset. We think of the world as a much smaller place than those that came before us. We are living in McLuhan’s global village, where one person’s actions can lead to a cascade of effects across the Globe: not through some disembodied “invisible hand,” but by the interaction of people who are known to each other. Our ability to influence those that we know means that what we do can propagate through the social matrix that shapes our world, and can open doors, shift political debate, or quell a rumor.

And because we know that this is how the world wags — that even the least networked of us is connected to everyone if he is connected to at least one other person — now, everything is different. So, we have lifted the title of Karinthy’s forgotten book to serve as the initial piece for this journal, dedicated to social networking in business, because now everything is different.

The world of business — where “networking” has been a gerund for decades — is rediscovering the latent power of social networks. Personal and business relationships are being reappraised in light of social networking technology and techniques, in ways that were too costly or simply impossible prior to the twenty-first century.

While the Facebook researchers nodded their heads at Milgrams work, I dug out this old piece and reproduced in its entirety, so that people can see that the idea is much older, and was originally projected to be five degrees, which is the approximate number offered up by this new research. And Milgram’s working hypothesis might just as well have been rounded down to 5, as well.

There is no doubt that as people become more socially connected, as a general rule, the mean path length across the entire world will drop. As that happens, the world grows smaller, and what happens to someone far away can feel as if it was next door.

We can only hope that this will lead to a great sense of community and solidarity, instead of the squabbling and feuding that dominates world affairs.

related

(Source: infoneer-pulse)

The Famous Are Different From You And Me

Shea Bennett via AllTwitter

A recent study from Hubspot has determined that while highly-followed Twitter accounts share a lot of links, they converse less frequently than people who follow less than a thousand people.

Twitter accounts with a million or more followers tweet links three times more frequently than users with 1,000 followers or less, but only about 7% of their tweets are replies, compared with 17% for those with the smaller network.

via visually

I am not sure of the conclusion, that conversation doesn’t grow reach. These twitterers, with a million plus followers, are generally followed for something other than their curatorial and social skills: they are famous for their looks, acting, fiction, music, or some other notoriety. People follow them for completely different reasons than, say, following me.

Better to paraphrase F Scott Fitzgerald, and say that the famous are different from you and me.

I’d like to see a study about twitterers that are a/ not famous for something else, but b/ have amassed large following (more than 10,000 followers). What works for them might lead to better insights for the average joe who wants more followers.

The other findings are interesting, too: a lot of the social gestures in social media — likes, comments, and so on — don’t lead to more views. So, a person who has a dense network of involved friends might not be growing her network as a function of that network’s activities. This is a problem suitable for social network graph analysis, because all networks are not alike, and popularity isn’t the only way to measure impact (see It’s Betweenness That Matters, Not Your Eigenvalue: The Dark Matter Of Influence).