Tag Archives: Network

If Facebook were a country, it would be the third largest country in the World!

According to stats published by Facebook, Facebook has currently 400,000,000 active users. This would make it the third most populous country in the world, after China and India.
Do you bet it will overtake India’s population (1,166,900,000)? In how many months?
(picture adapted from this image)

Networks of loneliness

Pretending not to. Social networks as covers (both for love and work)

Great paper by Mikolaj Jan Piskorski (Harvard Business School) “Networks as Covers: Evidence from business and social On-line Networks” . Amazing which patterns everybody can unveil when (almost) all out social interactions leave electronic trails everybody can collect and analyze! Amazing and of course scary!

This paper proposes that networks can act as covers which allow actors to participate in markets while maintaining a plausible excuse that they are not. Most generally, a cover is any action which allows ego to signal to alter that he is of type A when in reality they are of type B.

Evidence from Linkedin: “LinkedIn allows people who are currently employed to go on the job market without looking like they are on the job market. Recruiters are attracted to LinkedIn because they can obtain access to people who are ordinarily very hard to find in the labor market. Interviews with employers reveal that they are aware of this function of LinkedIn, and lose their employees this way.

Evidence from another network (the paper does not explicit which one but says “the network has been designed largely for people to keep in touch with their friends, and not for business purposes. Results indicate that almost 70 per cent of all activity on this on-line network is related to viewing profiles and pictures of others.”, so I might guess the network is Facebook, wondering why Mikolaj didn’t write which is the network… ): Men in particular look at pictures of women they do not know. Furthermore, regression analysis shows that men who publicly declared themselves to be in a relationship are more likely to examine profiles and pictures of women they do not know. Consistent with the view of networks as covers, (…) men in relationships and with large on-line networks are more like to look at women they do not know. In contrast, single men with large networks are more likely to look at women they do know. Implications for network theories as they pertain to organizations are explored.

Credits for picture: pagedooley from Flickr Creative Commons released

Happiness as a contagious virus: please spread it!

Leave a reply

Some papers are more worth than others.
Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study by James H Fowler and Nicholas A Christakis.
Solid analysis based on data from 4739 individuals followed from 1983 to 2003.

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.

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

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.

(credits: Photo by beija-flor released on Flickr under Creative Commons Attribution Noncommercial No Derivative license)

Calvino’s invible cities and their web of relationships

Leave a reply

(Image from Maggie Digital, released under Creative Commons BY-NC-ND)

Quote from Calvino’s Invisible Cities

In Ersilia, to establish the relationships that sustain the city’s life, the inhabitants stretch strings from the corners of the houses, white or black or gray or black-and-white according to whether they mark a relationdhip of blood, of trade, authority, agency. When the strings become so numerous that you can no longer pass among them, the inhabitants leave: the houses are dismantled; only the strings and their supports remain.
From a mountainside, camping with their household goods, Ersilia’s refugees look at the labyrinth of taut strings and poles that rise in the plain. That is the city of Ersilia still, and they are nothing.
They rebuild Ersilia elsewhere. They weave a similar pattern of strings which they would like to be more complex and at the same time more regular than the other. Then they abandon it and take themselves and their houses still farther away.
Thus, when traveling in the territory of Ersilia, you come upon the ruins of abandoned cities, without the walls which do not last, without the bones of the dead which the wind rolls away: spiderwebs of intricate relationships seeking a form.