Networks not Markets, Cliques not Classes: The Promise of Big Data

by Prof. Alex `Sandy’ Pentland, MIT Media Lab

Adam Smith and Karl Marx were wrong — or at least they only had half the story. The daily ebb and flow of our societies is the sum of billions of individual exchanges — people trading information, money, goods, or just gossip.   When we average over these billions of individual events we obtain the familiar groupings we call markets and classes as well as statistics such as market prices or percentages of voters.  These averages and groupings were the foundations for the grand theories of the Enlightenment and remain the subject of most social theorizing and political reasoning.

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Big Data: Toward A Richer Social Science

ABUJA, COTE D’IVOIRE.   Arnaud, a sergeant in the city police force, was worried about rising ethnic tensions. With a few key strokes on his computer, he mapped the boundaries between the feuding ethnic groups and altered the daily patrol schedule to focus more on those areas. Sandrine, who managed the local public health systems, was working to contain a recent outbreak of an infectious disease in one of the city’s shantytowns. With a few key strokes she pulled up a map of daily mobility patterns in and out of the shantytown, and then alerted the clinics where the disease was most likely to appear next. Moussa, an administrator for the city bus system, was concerned about rising overcrowding along certain routes. So he called up a map of the aggregate home-work transit patterns and discovered that they had significantly changed in the last month. Using this updated information, he began to change the bus routes to better handle the daily commute.

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Beyond viral

The golden age of social media coincides with a worldwide leadership crisis, manifested by our seeming inability to address any major global issue in recent years (WEF 2014). These days, no one – be they a charismatic leader or a nameless crowd – seems to be able to make issues popular for long enough to mobilize society into action. As a result of this leadership vacuum, social progress of all sorts seems to have become stymied and frozen. How can this happen precisely in a time when social media, praised as the ultimate tool to raise collective awareness and mobilize society, has reached maturity and widespread use? Here we argue that the co-existence of social media technologies with ‘The End of Power’ (Naim, 2014) is anything but a coincidence, presenting the first techno-social paradox of the 21st century.

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Limits of Social Learning

Online social networking may have started out as a simple way to share news, but has become much more than that. A whole industry has sprung from the impact social media can have on people’s behavior. Scientists are exploring how to capitalize further on its potential to inspire change in people’s purchasing habits through viral marketing, and to solve difficult problems such as increasing voter participation, and searching large geographies for objects or people.

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A letter from the Social Search frontier: Good news, Bad news

By Manuel Cebrian & Iyad Rahwan.

Our ability to search social networks for people and information is fundamental to our success. We use our social networks to look for new job opportunities, to seek advice about what products to buy, to find a good physician, to identify business partners, and so on. For some reason, we seem to be able to search social networks efficiently, and we only need a few introductions before finding the answer to our question, or the kind of person we are seeking. How come?

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Ecology and Topology in the Financial World – Part III

by Yaniv Altshuler

In the previous post we have shown the topology and money flow dynamics of the financial system in the U.S. This data, operated by the Federal Reserve System, represents approximately 9,500 participating banks transfer funds. The sample from this network amounted to around 700,000 transfers, with just over 5,000 banks involved on an average day.

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Ecology and Topology in the Financial World – Part II

In the previous post we learned about the importance of taking interconnections between market players while performing a risk assessment process. As mentioned, this fact is not unique to banking or trading platforms, as pointed out in the “Ecology for Bankers” paper by May et. al. In this paper, the authors have presented an interesting analogous situation, in the form of fisheries management. For the past half-century, investments in fisheries science have focused on management on a species-by-species basis (analogous to single-firm risk analysis). With collapses of some major fisheries, however, this approach had gave way to the view that such models may be fundamentally incomplete, and that the wider ecosystem and environmental context (by analogy, the full banking and market system) are required for informed decision-making. This, in fact, coincides with the broader understanding that emerges nowadays in many areas of applied science, acknowledging the need for a larger-system perspective.

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Ecology and Topology in the Financial World

“‘Tipping points’, ‘thresholds and breakpoints’, ‘regime shifts’ — all are terms that describe the flip of a complex dynamical system from one state to another. Catastrophic changes in the overall state of a system can ultimately derive from how it is organized — from feedback mechanisms within it, and from linkages that are latent and often unrecognized. The change may be initiated by some obvious external event, such as a war, but is more usually triggered by a seemingly minor happenstance or even an unsubstantial rumor. Once set in motion, however, such changes can become explosive and afterwards will typically exhibit some form of hysteresis, such that recovery is much slower than the collapse.”

These are the opening lines of the stimulating paper “Ecology for Bankers” (May et. Al, Nature, 2008), that attempts to explore the roots of the 2008 economic crisis, and try to understand how (if at all possible) it could have been avoided.

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Hubs and Centers of Information

by Yaniv Altshuler

In order to understand the importance of small world networks and specifically – its relevance to computational social finance, let us first take a metaphoric detour and discuss film actor Kevin Bacon. After having played in numerous films, in an interview held in 1994 Bacon commented that he believed he had worked with every actor in Hollywood either directly, or through another single connecting actor. Shortly after this comment, an internet newsgroup bearing the title “Kevin Bacon in the Center of the Universe” appeared, discussing the validity of this declaration. Becoming somewhat of an urban legend, this theory had gained increasing popularity, resulting in numerous discussions, parodies and even a trivia game and a charity organization (founded by Kevin Bacon himself).

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Six Degrees Of Separation

by Yaniv Altshuler
 

“What a small world indeed!” we say when discovering that a person we’ve just met used to study at our high-school, or has a relative that used to worked with us a few years ago. But just how small is it?

It was this question that drove Stanley Milgram and his colleagues back in 1967 to conduct what would be later called “Milgram’s experiment”. With the desire to understand the connections that form the basis of our communities, Miligram and his crew chose random individuals in the U.S. cities of Omaha, Nebraska and Wichita, Kansas and asked them to assist in forwarding a package to an individual in Boston, Massachusetts. This was done by either sending the package directly to the destination in case the sender knew the destination personally, or sending the package to some friend or relative of the sender who may be more likely to know the target personally (with the instructions required to continue the process from this point). When (and if) the package eventually reached the contact person in Boston, the researchers could track its exact course. What interest the researchers was to find out the probability that two randomly selected people would know each other, or alternatively – what is the “average shortest path” between any two random people. The results that were obtained by analyzing the paths of the packages that reached the target yielded an average path length of little less than 6 (which led to the coining of the phrase “six degrees of separation”, referring to the distance between any pair of people at the U.S).

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Small World Networks

by Yaniv Altshuler

As mentioned in the previous post, social trading networks are networks that connect people. As a result, these networks tend to follow the way people make social interactions. One of the most thrilling and important revelations of complex networks research in the past decade is the fact that in a social network – every two strangers can be connected by a usually very short chain of mutual friends. This principle is called “The Small World Phenomenon”, and characterizes many of complex networks we encounter in our daily life.

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Complex Networks

In the previous post, I have presented the general concept of “networks”, and discussed their broad use in a great variety of scientific domains, due to their high flexibility, that enables network to be used as a basic building block in many model or more complicated analytic structures. This flexibility, however, may sometime baffle the novice researcher, as different types of networks may present very different kinds of behaviors and properties.

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Networks

by Yaniv Altshuler

Previously, I have mentioned several times the term Trading Network. At first glance this term me intuitively seem self explanatory, as when asked to define it, most people would likely depict it as a “network” (in the sense of a group of people, or a service), that is used for the purpose of financial trading. However, in order to continue with our methodological understanding of social trading, we should formally understand what a “trading network” is. Whereas its second half (i.e. “trading”) describes the functional purpose of the term, its first has is associated with one of the most fundamental aspects in current research – networks.

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Social networks influence the decisions of financial traders

by Yaniv Altshuler

One of the great innovations that lay in eToro’s OpenBook platform is the social-financial entanglement that resides in its core, being derived from the interplay between an open social network and a financial trading system. Having the inherent ability to share ideas and information between each others, OpenBook’s users are given a nre source of information they can use in order to enhance their trading performance. As the users are not playing against each other but rather – against the market, this situation becomes a non zero-sum game, hence incentivizing the users to share as much information as possible. In my research I am interested in observing this process, and the value it encapsulates.

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Social mobilization from the Twittersphere

by Esteban Moro

While public demonstrations are Social Science’s most important and studied phenomena, they are also the most mysterious and poorly understood ones. Demonstrations trigger new social movements, change countries attitudes, and have the potential to overthrow governments. Despite these social expressions being people’s most powerful force, very little is known about how they form, why the form, and most importantly, who they are formed by.

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