Twitter changes itself from a social network into a news app.

The company appears to be looking to give itself more visibility, after disappointing results and growing concern about its direction.


Twitter has stopped calling itself a social network, and instead will think of itself as a news app.

Its official app has been moved out of its traditional and perhaps expected category – social networks – and instead will sit alongside more traditional news outlets.

The company has simply made the move on the App Store, and it will likely help it get more visibility and therefore downloads. But it comes at a time of increasing concern about Twitter’s future, and could be the first part of a major change in strategy for the site.

The company hasn’t made any public statement about why it made the change.

But among other things, it means that Twitter will no longer sit next to – and below – other more popular social media apps like Facebook and its various apps.

Instead, it will sit mostly with news organisations, most of which have their own apps, and will easily compete with many of those.

It might also signal a move in strategy for Twitter. The site has mostly been judged against Facebook and other networks on the basis of traditional measures like how many active users it has per month and how much money it can generate through ads, but will now be able to say that it rejects that comparison.

After the move, Twitter might be able to shift the focus onto its role in news gathering and breaking. The company has been increasingly concerned to stress how central it can be in news events, a fact that it built on with the recent release of its Moments too, which aggregates tweets about a certain topic and allows people to read them as a story on the app or site.

Facebook Use Predicts Declines in Subjective Well-Being in Young Adults.


Over 500 million people interact daily with Facebook. Yet, whether Facebook use influences subjective well-being over time is unknown. We addressed this issue using experience-sampling, the most reliable method for measuring in-vivo behavior and psychological experience. We text-messaged people five times per day for two-weeks to examine how Facebook use influences the two components of subjective well-being: how people feel moment-to-moment and how satisfied they are with their lives. Our results indicate that Facebook use predicts negative shifts on both of these variables over time. The more people used Facebook at one time point, the worse they felt the next time we text-messaged them; the more they used Facebook over two-weeks, the more their life satisfaction levels declined over time. Interacting with other people “directly” did not predict these negative outcomes. They were also not moderated by the size of people’s Facebook networks, their perceived supportiveness, motivation for using Facebook, gender, loneliness, self-esteem, or depression. On the surface, Facebook provides an invaluable resource for fulfilling the basic human need for social connection. Rather than enhancing well-being, however, these findings suggest that Facebook may undermine it.


Within a relatively short timespan, Facebook has revolutionized the way people interact. Yet, whether using Facebook predicts changes in subjective well-being over time is unknown. We addressed this issue by performing lagged analyses on experience sampled data, an approach that allowed us to take advantage of the relative timing of participants’ naturally occurring behaviors and psychological states to draw inferences about their likely causal sequence [17][18]. These analyses indicated that Facebook use predicts declines in the two components of subjective well-being: how people feel moment to moment and how satisfied they are with their lives.

Critically, we found no evidence to support two plausible alternative interpretations of these results. First, interacting with other people “directly” did not predict declines in well-being. In fact, direct social network interactions led people to feel better over time. This suggests that Facebook use may constitute a unique form of social network interaction that predicts impoverished well-being. Second, multiple types of evidence indicated that it was not the case that Facebook use led to declines in well-being because people are more likely to use Facebook when they feel bad—neither affect nor worry predicted Facebook use and Facebook use continued to predict significant declines in well-being when controlling for loneliness (which did predict increases in Facebook use and reductions in emotional well-being).

Would engaging in any solitary activity similarly predict declines in well-being? We suspect that they would not because people often derive pleasure from engaging in some solitary activities (e.g., exercising, reading). Supporting this view, a number of recent studies indicate that people’sperceptions of social isolation (i.e., how lonely they feel)—a variable that we assessed in this study, which did not influence our results—are a more powerful determinant of well-being than objectivesocial isolation [25]. A related question concerns whether engaging in any Internet activity (e.g., email, web surfing) would likewise predict well-being declines. Here too prior research suggests that it would not. A number of studies indicate that whether interacting with the Internet predicts changes in well-being depends on how you use it (i.e., what sites you visit) and who you interact with [26].

Future research

Although these findings raise numerous future research questions, four stand out as most pressing. First, do these findings generalize? We concentrated on young adults in this study because they represent a core Facebook user demographic. However, examining whether these findings generalize to additional age groups is important. Future research should also examine whether these findings generalize to other online social networks. As a recent review of the Facebook literature indicated [2] “[different online social networks] have varied histories and are associated with different patterns of use, user characteristics, and social functions (p. 205).” Therefore, it is possible that the current findings may not neatly generalize to other online social networks.

Second, what mechanisms underlie the deleterious effects of Facebook usage on well-being? Some researchers have speculated that online social networking may interfere with physical activity, which has cognitive and emotional replenishing effects [27] or trigger damaging social comparisons[8][28]. The latter idea is particularly interesting in light of the significant interaction we observed between direct social contact and Facebook use in this study—i.e., the more people interacted with other people directly, the more strongly Facebook use predicted declines in their affective well-being. If harmful social comparisons explain how Facebook use predicts declines in affective well-being, it is possible that interacting with other people directly either enhances the frequency of such comparisons or magnifies their emotional impact. Examining whether these or other mechanisms explain the relationship between Facebook usage and well-being is important both from a basic science and practical perspective.

Finally, although the analytic approach we used in this study is useful for drawing inferences about the likely causal ordering of associations between naturally occurring variables, experiments that manipulate Facebook use in daily life are needed to corroborate these findings and establish definitive causal relations. Though potentially challenging to perform—Facebook use prevalence, its centrality to young adult daily social interactions, and addictive properties may make it a difficult intervention target—such studies are important for extending this work and informing future interventions.


Two caveats are in order before concluding. First, although we observed statistically significant associations between Facebook usage and well-being, the sizes of these effects were relatively “small.” This should not, however, undermine their practical significance [29]. Subjective well-being is a multiply determined outcome—it is unrealistic to expect any single factor to powerfully influence it. Moreover, in addition to being consequential in its own right, subjective well-being predicts an array of mental and physical health consequences. Therefore, identifying any factor that systematically influences it is important, especially when that factor is likely to accumulate over time among large numbers of people. Facebook usage would seem to fit both of these criteria.

Second, some research suggests that asking people to indicate how good or bad they feel using a single bipolar scale, as we did in this study, can obscure interesting differences regarding whether a variable leads people to feel less positive, more negative or both less positive and more negative. Future research should administer two unipolar affect questions to assess positive and negative affect separately to address this issue.

Concluding Comment

The human need for social connection is well established, as are the benefits that people derive from such connections . On the surface, Facebook provides an invaluable resource for fulfilling such needs by allowing people to instantly connect. Rather than enhancing well-being, as frequent interactions with supportive “offline” social networks powerfully do, the current findings demonstrate that interacting with Facebook may predict the opposite result for young adults—it may undermine it.

Source: PLOS one






Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study.


Objectives To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks.

Design Longitudinal social network analysis.

Setting Framingham Heart Study social network.

Participants 4739 individuals followed from 1983 to 2003.

Main outcome measures Happiness measured with validated four item scale; broad array of attributes of social networks and diverse social ties.

Results Clusters of happy and unhappy people are visible in the network, and the relationship between people’s happiness extends up to three degrees of separation (for example, to the friends of one’s friends’ friends). People who are surrounded by many happy people and those who are central in the network are more likely to become happy in the future. Longitudinal statistical models suggest that clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals. A friend who lives within a mile (about 1.6 km) and who becomes happy increases the probability that a person is happy by 25% (95% confidence interval 1% to 57%). Similar effects are seen in coresident spouses (8%, 0.2% to 16%), siblings who live within a mile (14%, 1% to 28%), and next door neighbours (34%, 7% to 70%). Effects are not seen between coworkers. The effect decays with time and with geographical separation.

Conclusions People’s happiness depends on the happiness of others with whom they are connected. This provides further justification for seeing happiness, like health, as a collective phenomenon.


What is already known on this topic

  • Previous work on happiness and wellbeing has focused on socioeconomic and genetic factors
  • Research on emotional contagion has shown that one person’s mood might fleetingly determine the mood of others
  • Whether happiness spreads broadly and more permanently across social networks is unknown
  • Happiness is a network phenomenon, clustering in groups of people that extend up to three degrees of separation (for example, to one’s friends’ friends’ friends)
  • Happiness spreads across a diverse array of social ties
  • Network characteristics independently predict which individuals will be happy years into the future

What this study adds



Source: BMJ


Bring your social network home with Nextdoor.




Remember the days when neighbors knew each other by name, shared a cup of sugar or a hammer, discussed issues facing their neighborhood or babysat each other’s children?

This sort of neighborliness may still exist to some extent in some places, which is great. But as more people turn inward into digital lives and real-world connections erode, why not harness the best practices of social networks and apply them toward advancing that neighborhood ideal? Neighborhoods were the original social networks, after all.

That’s what Nirav Tolia, co-founder and CEO of Nextdoor, a social network for the neighborhood, wondered. “Technology has done such an amazing job at making it easier to connect to people we’re distant from,” he muses, during a chat at the Nextdoor offices in San Francisco. “Technology has not done a great job at putting us in contact with people right at our front doors.”

The premise is simple: Nextdoor is a private social network for you and your neighbors. You can post about a chair you want to sell, provide information about a dance recital, look for advice on a good electrician, invite your neighbors over for a cocktail, share coupons — how you use Nextdoor is really up to you. You can include nearby neighborhoods or “mute” areas or people you don’t care to hear from.

You can think of Nextdoor as part Craigslist, part Angie’s List, part early Facebook, part Neighborhood Watch, and part coffee-shop bulletin board.

Why not use Facebook or a listserv to talk to neighbors or rely on Craigslist to get ride of your unwanted bookshelves? Some people don’t believe Facebook will protect personal information, while listservs and Google groups are too general and Craigslist is too anonymous.

Nextdoor is unique in that it’s totally private once you’re in (no SEO). Each potential Nextdoor member must have their real name and address verified (via postcard or credit-card billing statement). A neighborhood must have at least 10 neighbors verified to become official. “You have to nail privacy. People are talking about their homes, their addresses, their children — they have to feel comfortable sharing,” Tolia says.

There’s another practical reason that there is a place for Nextdoor: Facebook doesn’t always identify who might be living next-door. “Any platform that has what we call a synchronous friending model will not work in neighborhoods,” he notes. “If I don’t know my neighbors, how can I connect to them?”

Nextdoor relies on neighbors inviting their neighbors. If residents want to get in touch with someone they don’t know, Nextdoor issues offline invitations like postcards and fliers that can be personalized and mailed.

Tolia is surprised that 40 percent of the initial content on Nextdoor is transactional. Another use that caught him off-guard is the platform’s role in public safety. Some members are creating virtual neighborhood watches, where they discuss crime and then mobilize in the real world. About 100 police departments are integrated into Nextdoor communities. Police cannot see what is posted, but they can share their own PSAs or crime updates.

So far, Tolia’s team has raised about $40 million from venture capitalist social experts Greylock and local niche experts Benchmark Capital, and Nextdoor users are trading almost one million messages daily in more than 11,000 neighborhoods in all 50 states. The cash should last for five or so years while the site grows, but Tolia says the team is throwing around ideas about how to collect revenue over the long term.

“The recommendations area is ripe for local advertising,” he explains. “We’re thinking about ways to create a place for those merchants who used to use yellow pages.”

Nextdoor wants to bring people closer, one neighborhood at a time.

Source: Smart planet


Q&A: Why you have fewer friends than your friends do on Facebook.

With its one billion user mark hit yesterday, Facebook is closer to its mission of making the world more connected. And it appears to be literally changing the long-held idea of six degrees of separation, which states that everyone is no more than six steps from any other person on Earth. Researchers have found that within the Facebook community, that key number shrinks to just over four steps. This is just one finding of many coming out of an enormous study of 721 million active users on Facebook led by a group at Cornell University in collaboration with Facebook’s Data Science team. With such an embarrassment of social connection riches, the researchers have uncovered fascinating patterns and quirks of human and social behavior.

If you’ve felt not-as-popular as your friends on Facebook, you are right. Typically your friends will have about three times as many friends as you. Why? Well it has to do with math and statistics, and the research teams have proven that it plays out consistently within the Facebook network.

SmartPlanet spoke with Johan Ugander, a PhD candidate at Cornell’s Center for Applied Mathematics, and asked him to explain this friendship paradox, as well as reveal other findings about our social natures from this massive study.

SmartPlanet: One of the fascinating things is that, and you got this from the Facebook data, if all the people on a four-person list came from separate social groups (eg, from your high school, or work, or family) then the likelihood of someone being influenced by those people was more than twice as likely than if all the people were from the same social group (eg, all co-workers.)

Johan Ugander: Right. Facebook promises this opportunity in resolving incredibly data demanding questions in the social sciences. So we studied Facebook’s data and how millions of individuals are making decisions about joining Facebook.

And you found a very interesting quality of social decision-making, right?

Yes, we specifically looked at the invitation mechanism. Say you’re invited to Facebook, and they show you a number of different faces, faces of people already on Facebook. And the thing that really surprised us was that the dominant driving force was not how many unique social contacts that invited you.

It was some quality of those social contacts?

We found is that if there are two people that are part of this invitation community, and if those two people come from different social contexts, you’re fifty percent more likely to accept the invitation than if they’re from the same context.

So you mean that if two people are in the welcome invite to Facebook and one is from your high school context and the other is a co-worker you are twice as likely to join than if those two people were both family members?

Right. The basic motivation of this is that people that are from the same context are essentially redundant. So if your brother and sister are both recommending you a book, you don’t really take them as independent sources of information. But if you co-worker and your siblings recommend you a book, that’s a much stronger recommendation, because now it’s sort of reached you from two independent directions.

Fascinating. What are the practical implications of this?

With health practices, researchers are trying to figure out how to convince people to start using good health practices. Another obvious application is to help business spread ideas. And a recent study where the Facebook team studied the spread of voter participation, and it also showed that there is a big social component to voting.

Can you talk a bit more about Facebook’s research teams and what their motivations are?

Facebook has a research group called the Data Science team that helps to guide the product to its next levels. The Science Team has really grown since 2010.

And you started working with them in 2010 right?

One of the big papers that we put out in 2010 is this large-scale study where we asked a wide range of empirical questions about Facebook as a social network.

We were sitting on the largest social network data set, this treasure trove of data. So we asked a lot of the same questions social researchers have asked before, but now we were asking at a Facebook scale.

And what was one of those questions?

Well it has to do with the famous notion of six degrees of separation. With Facebook we have something resembling the complete graphic world, we have ten percent of the world’s population.   So how far apart are people?  Is it six degrees?

And was it?

No. In fact the average distance between any two people on Facebook was 4.74. But also we found these results had been shrinking over the the past three years, since 2007, the average distance between two people has been shrinking. This is related to Facebook’s mission of making the world more open and connected. A lot of people at Facebook were happy to see this.

Yes, Facebook has actually making the world smaller, by allowing relationships to flourish online, globally.

Another question that we wanted to ask was this notion of your friends always have more friends than you.

Right. That is fascinating, that no matter what, on Facebook your friends on average, will always have more friends than you have. It might seem depressing.

It’s called the “friendship paradox”. If you look across your friends, surprisingly often you have fewer friends than your friends do. And this is derived from a mathematical theorem.

And you found that the math worked in reality?

Yes we found that 93 percent of Facebook users have fewer friends than their friends. So it’s a mathematical fact, not something one should be depressed about.

Consider this metaphor: It happens for the same reason that when you go to the gym, you see only the fit people, and when you look at your friends on Facebook you see only people who are social.

You mentioned that Facebook users have an average number of 190 friends. But their friends average 635 friends. Now, when you say their friends average, are you talking about their total number of friends or are you talking about each individual friend added up? This is where it gets tricky.

Exactly, this is where it gets tricky. If you select a person at random and you get an average number of friends at 190. But if you look at a random friend of a random user, you’re biasing your selection towards people who have a lot of friends. You’re much more likely to hop to somebody who has a lot of paths leading to them. Somebody who has ten thousand friends is going to show up much more in your sample than somebody who only has two friends.

The gym metaphor helps here.

Right,  if you go to the gym you’re only seeing the people who go to the gym often. The couch potatoes are only going to the gym once a month, so on your average visit you’re not going to see them, whereas you’re going to see the person who’s there everyday.  And you might feel bad about your physique.

What would be a practical implication for the “friendship paradox”?

Well for Facebook there are implications. These factors of friends grow very quickly. Take a person with a 100 friends, and you think OK, their friends have about a hundred friends each, so you’d expect them to have 10,000 friends of friends, which is 100 x 100. But in reality a person with a hundred friends has twenty-seven thousand friends of friends, close to three times more than you would expect. This paper provided Facebook’s engineering people information on how some of these properties behave on Facebook.

What are Facebook’s goals with this research arm?

The Data Science team has an ambition to do a complete overhaul of these questions in social science and social psychology because it has a huge treasure trove of data. The research is useful for the design of products and recommendations that Facebook offers.

But on the academic side, the social science hypotheses that have been around for decades we can now get numbers for. And there’s a long list of studies that we’d like to run.

Source: Smart Planet.

Amygdala at the centre of your social network

A larger emotion-processing brain centre is linked to a bigger circle of friends.


AmygdalaThe size of your amygdala (circled) indicates the extent of your social network.Brad Dickerson

How many friends do you have? A rough answer can be predicted by the size of a small, almond-shaped brain structure that is present in a wide range of vertebrates, scientists report today in Nature Neuroscience.

The researchers studied the amygdala, which is involved in inter-personal functions such as interpreting emotional facial expressions, reacting to visual threats and trusting strangers. Inter-species comparisons in non-human primates have previously shown that amygdala volume is associated with troop size, suggesting that the brain region supports skills necessary for a complex social life1.

On the basis of these past findings, psychologist Lisa Feldman Barrett of Northeastern University in Boston, Massachusetts, wondered whether a larger amygdala size allows some humans to build a richer social world.

Barrett’s team measured the amygdala volume in 58 healthy adults using brain images gathered during magnetic resonance imaging sessions. To construct social networks, the researchers asked the volunteers how many people they kept in regular contact with, and how many groups those individuals belonged to.

They found that participants who had bigger and more complex social networks had larger amygdala volumes. This effect did not depend on the age of the volunteers or their own perceived social support or life satisfaction, suggesting that happiness is not the underlying causal factor that links the size of this brain structure in an individual to their number of friends2.

“We’d all predict this relationship should be found, but [the authors] did it in a very smart way by ruling out other variables,” says cognitive neuroscientist Kevin Ochsner of Columbia University in New York City. “That’s why I think this paper is going to end up being a citation classic, because it demonstrates the relationship in a way that gives you confidence that it’s real,” he adds.

Brain teaser

But it’s still a mystery how the amygdala contributes to social networks. Perhaps the structure’s response to faces, emotions or emotional memories influences whether someone decides to develop and maintain relationships, says Brad Dickerson, a cognitive neuroscientist at Massachusetts General Hospital in Boston, who helped lead the study.

It’s likely that social behaviour relies on a much broader set of brain regions, Dickerson says. In the future, the team will use functional neuroimaging approaches to determine the relationship between patterns of brain activity in an individual and the size of social groups to which they belong.

Another important question is whether a big amygdala is a cause or a consequence of having a large social network. “In the end, it’s probably some of both,” Ochsner says. “But you first had to establish that the relationship really exists before you could address those critical questions.”


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