Facebook in Decline

Facebook has seen consistent growth over the past few years, but it has recently seen this growth peak. The number of users is now declining, down nine million monthly users in the United States. The number of minutes that Americans spend on Facebook has also declined; however, growth in India and Brazil has increased. It is possible that growth has stopped in America due to Facebook reaching its peak and that other countries are still catching up.

Another explanation offered is the adoption of smart phones in Brazil and India which in turn has led to adoption of Facebook as a mobile app. This pattern is similar to the idea of information cascades and adoption of technology in networks: as more people buy smart phones and begin using Facebook, it becomes more beneficial for others to do so as well, especially if the initial users are friends of later adopters. Adopting Facebook on new smart phones has a higher benefit as more friends join and can derive value from being able to interact with each other on the site.

FBI Soon to Be Watching Your Online Communications the Moment they Happen

A government task force is preparing legislation that would pressure companies such as Face­book and Google to enable law enforcement officials to intercept online communications as they occur, according to current and former U.S. officials familiar with the effort.

The FBI believes it does not have the capabilities it requires to tap and trace internet communications of potential terrorists, and is proposing to fine companies that fail to comply with wiretap orders. They believe that suspect’s activities can be missed as critical evidence.

The draft of the proposal states that a court can levy a series of escalating fines in firms that fail to comply with wiretap orders. Companies that do not comply with an order within a certain period would face an automatic judicial inquiry. After 90 days, fines that remain unpaid could lead to fines.

The proposal would not dictate how the wiretapping capability must built and leaves the development to the companies. Small companies are exempt from fine.

As I read this article and many other on CISPA and the previous SOPA bill have me curious as to the capabilities of the federal government when they have control of all the information pertaining to the nodes of the network and the direction in which the edges between them travel. The private companies have the capability to do that, but only for their services. What happens when both graphs overlap and a more detailed and defined graph is formed? The information that could be learned from this overlapping of graphs would critical to understanding the human network.

Yours Truly,

G.Vas

http://www.washingtonpost.com/world/national-security/proposal-seeks-to-fine-tech-companies-for-noncompliance-with-wiretap-orders/2013/04/28/29e7d9d8-a83c-11e2-b029-8fb7e977ef71_story.html

Finding the Easy Way to Do Hard Things

This past week I came across a research paper by Nicholas Christakis and James Fowler in which they discuss their testing of a means for detecting disease outbreaks early in their development.  They start from the idea that individuals who are more central to the network are more like likely to be close (as measured in terms of the number of edges) to the individual who introduces a disease into the network, therefore will catch the disease earlier.

Here’s the super-clever part.  Looking at previous research on and attempts at heading off outbreaks, they concluded that actually mapping a social network is too slow and onerous a task to be useful.  Epidemics can move quickly, and large social networks can be very difficult to map.  Instead, they pursued a much easier process for determining who in a network is more central.  Taking advantage of the “friendship paradox” (as they describe it, the strange fact that “your friends have more friends than you do”), they took a random sample of Harvard undergraduates and asked them to name a friend.  This second sample, not the original, randomly chosen students but the friends of the randomly chosen students, should theoretically exhibit greater centrality than the random selection, meaning that this group will generally be closer to the source of the disease and therefore catch it sooner.  They tested this using students at Harvard during a flu outbreak and found that they were correct; the epidemic peaked earlier in the second group than in the first.

What I find intriguing and important about this work is that they manage to reveal information about the network structure without actually having to map the network.  As we’ve learned during this past semester, there are many common, stable properties of networks that could be used to make predictions about network behavior.  However, this is often useful only so long as one has a map of the network.  By teasing out an easily discoverable group that exhibits higher than average centrality, the researchers were able to use this group as a “sensor” for coming outbreaks of the flu.  This reminds of me of what Dr. D when we were studying the adoption of new technologies that have network effects; our abstract quantitative understanding of the phenomenon, which is dependent on having information we would never have in the real world, points us in the direction of a qualitative understanding that is easily applied in the real world.  Similarly, Christakis and Fowler’s approach allows for one to make potentially powerful predictions about the spreading of a contagious disease within a network without having to do the difficult-to-impossible work of precisely mapping the network.

(Christakis happens to also have given this related TEDTalk)

Golden Age for Science of Social Networks: Bountiful Applications

 

Clever social scientists are coming up with new ways to put the burgeoning amounts of data on social networks to work for societies they are supposed to reflect. By employing the help of inquisitive physicists these psychohistorians are analyzing patterns in the network dynamics we’ve discussed in general models, and refining models to study at far more precise levels. A researcher at Northeastern University has managed to devise an algorithm that analyzes a person’s mobile-phone records and then with 93% accuracy predict where that person will be at any point during the day. In another interesting application Dr. Vesipigani along with his team have created a program named GLEAM (Global Epidemic and Mobility Model) which splinters the world into hundreds of thousands of squares. Using these squares as hubs the program models travel patterns between other squares (busy roads, flight paths, etc.,) which demonstrated potential in 2009 when it successfully mimicked an outbreak of a strain of influenza known as H1N1 as it made its way across different countries with commendable accuracy. Within the guts of these models there are apparent network components such as transiency and network flows at work. The idea of using the rich new sources of data from mobile technology to model social network dynamics aspires to achieve such lofty goals as to predict potential tipping points where riots might break out, or model the breakdowns of trust between banks and customers that cause financial crises. I myself am interested to see how well we could use similar social network analysis to predict the business cycles of industry and performances within the market, perhaps measures of a firms social network could be revealing of sudden upticks in its market value.

Any thoughts are very welcome.

-Shane

The Economist: Dr Seldon, I Pressume

Cancer Epidemic?

We’ve been learning about epidemics this week, focusing on the way diseases cause epidemics through networks. We also learned ways in which these epidemics can be prevented. However, an article I found states that prosperity is what is causing a particular cancer epidemic in Latin America: “Latin America Threatened by Mounting Cancer Epidemic: Study” (source: http://health.yahoo.net/news/s/nm/latin-america-threatened-by-mounting-cancer-epidemic-study).

The article states:

A multinational team of researchers found the current state of cancer care and prevention in Latin America incompatible with the socioeconomic changes taking place in the region, where an increasingly urban populace faces mounting lifestyle-related cancer risks.

 Although cancer is not considered contagious, there are certain confirmed risk factors that will increase one’s chance of being diagnosed with cancer. In this case, prosperity is causing this region to imbibe in many cancer causing behaviors, such as drinking alcohol, smoking, eating until obese, and leading sedentary lives. Although this is extremely similar to the behaviors of Americans (who lead the world in obesity), and Latin Americans are less likely to contract cancer, they are twice as likely to die from it. This is due to their lack of preventative measures, lack of health care, and the patients seeking treatment too late.

The study recommended Latin American nations make major changes to their healthcare policies, such as dedicating more funds to public health, widening healthcare access so cancer patients can be treated earlier and developing better national cancer plans. It also envisions shifting funds away from costly end-stage cancer treatment toward palliative care.

 These are some of the ways that may help curb this ‘epidemic’, although this epidemic does not travel the way most diseases and epidemics do. The study calls for immediate change, otherwise it will be almost too expensive and deadly to deal with within a short span of just 10 to 15 years.

WoWconomics: Epidemics in the World… of Warcraft

Here we are friends, the final installment of your favorite weekly blog post: WoWconomics.

This article is not NEW, however, it is too relevant to ignore…

This week in class we learned about predicting the spread of epidemics through networks, and we have learned about several models that economists and scientists have developed to help model future outbreaks. However, we may need to look no further than the internet to find the best ways to model potential outbreaks, and with the help of the developers of World of Warcraft, Blizzard Entertainment, researchers have been able to see what an epidemic looks like in a real population. A population made out of fictional people.

World of Warcraft, in 2007, had an accidental glitch that mirrored a global epidemic more realistically than any model science had ever predicted, because it actually affected real people. When a virus called Corrupted Blood, which was supposed to be isolated to a separate part of the game, was accidentally introduced to the main population of an online server via an accidental teleportation by a player, it caused rampant destruction across tens of thousands of players in a matter of hours. Scientists have since looked back and attempted to model the viruses path across the server.

World of Warcraft offers a surprisingly close replica to our society in several ways that made this study particularly relevant. First, some players had access to abilities that allowed them to travel incredibly far in a short amount of time (similar to those few nodes in a network given long links) which allowed the disease to spread quickly across long distances. Additionally, characters were able to be re-infected, which some diseases allow for in reality as well. Also, some players acquired the disease and logged off immediately, and when they re-logged on at a later time, they still had the disease, allowing it to have longer gestational period than the game would allow. This mirrors real diseases in that some allow for people to be “carriers” and not succumb to the disease as quickly.

In the end, Blizzard fixed the problem by removing the disease from the game, claiming it was too dangerous for their players, but the real life implications of studying that disease have helped scientists see not only what a disease could do to a population, but also learn that potentially MMORPG games could be a suitable solution for scientific experimentation.

 

Link: http://www.time.com/time/health/article/0,8599,1655109,00.html

 

Reverse Epidemic Diffusion

In Wired magazines “Finding the Sources of Epidemics,” Samuel Arbesman discusses how networks can be used to find the source of an epidemic using as few as 20 percent of that network’s nodes. According to Mr. Arbesman “they (Pedro Pinto and his team) explore how the leader of a terrorist organization can be identified and even show how this methodology could be used in finding contamination sources in a subway system. They found that they could determine the source of a contamination to within a single subway stop by monitoring the behavior fewer than 20 percent of the stations.”

In this case, reverse diffusion was used to find the source of a cholera outbreak in S. Africa after the fact. However, models are one thing and their applications are quite another. In all of these examples except one, reverse diffusion is useful for finding a static hub. But no evidence backs the claim that the leader of a terrorist organization could be caught by working backwards with statistics. For one thing, the leader might move, making he or she harder to pinpoint than the proverbial hot zone subway stop this author mentions. Secondly, the leader might operate through proxy. Finally, reverse diffusion requires that 20 percent of the nodes in the network be analyzed. The last requirement is the most debilitating, because with sick people, the researcher can deal in absolutes – this person is ill and this one definitely is not. But how could this method be applied to something as complex as terrorism, where the researcher can’t be sure if their nodes are the right nodes? In terrorism, the researcher has to diagnose degrees of ideological infection, which is a far more abstract concept than a viral epidemic. http://www.wired.com/wiredscience/2012/08/finding-the-sources-of-epidemics/

Importance of Stopping H7N9

H7N9 is a new highly dangerous strain of influenza which originated  in birds, and now has infected 82 people and killed 17 in China.  What makes this virus so dangerous is because the symptoms are not apparent until several days after it is “caught”, and because the manner in which it spreads is still undetermined.

Fortunately, the way that epidemics are handled in the world today has vastly improved since the outbreak of SARS (also originating in China) ten years ago, which killed nearly 800 people.  A big reason that SARS infected so many people and caused such an international terror was because the Chinese government initially tried to cover up it’s existence, fearing the bans on travel and other sanctions from the World Health Organization and other international health authorities.  As technology has improved, so has the understanding of how these epidemics spread, which has lead to a decrease in the severity of the sanctions for infected nations.  The sanctions which remain are hardly detrimental to the host country, but still (hopefully) effectively quarantine infected persons to isolate the spread of the virus/disease.

The really interesting threat presented by H7N9 is its implications. If a person can merely become infected with H7N9 (or any other variant, future strain) by being in the general vicinity of, or having minimal physical contact with, an infected person, the world could be in a dire situation.  Due to globalization and cheap travel prices the amount of people who could become infected would balloon, possibly exponentially.  Our world population is enormous, and if history is any indication, mother nature has forms of checks and balances to keep population at a reasonable level.  If a new disease or virus was to originate in a country a little less experienced than China in handling epidemics, a real crisis could occur.

http://www.economist.com/news/science-and-technology/21576375-new-viruses-emerge-china-and-middle-east-world-poorly-prepared

No Hablo Spanish

My first language was Spanish but over the course of my life I have come to adopt English as my primary language of communication; it’s not like I had a choice, I was born in the United States. My Parents, not so, they’re from Puerto Rico and are as close to bilingual as you get. I on the other hand am less-so, not that I can’t understand Spanish its just that my upbringing involved having many more conversations in English than my “native” tongue. Therefore, while I can follow a conversation spoken in Spanish and understand it in near entirety, i simply cannot intelligently write Spanish, and many times, speak it. Unsurprisingly, i am not alone. A recent study concluded that less, relative to say 25-50 years ago, of the Hispanic population are results of first generation family members and more so are of second or third generation members who learned English as their first language and speak Spanish less than fluently. Univision has caught on: It has two Twitter feeds, one for its viewers that understand the programming, and another in English for those that need pointers. This applies to the information cascade on a very applicable sense because each prospective generation is tasked with the decision of whether or not to learn Spanish. In most parts of the United States where people predominantly speak English most immigrants will chose to teach their kids English because that’s what everyone speaks so the direct benefit of speaking English is that you can converse with everyone. Even yet, a recent Pew poll concluded that 95% of Hispanics believe that it is “important for future Hispanics to speak Spanish”, a surprisingly high number for a group of people who are seemingly doing less to pass on a language from generation to generation. I was also thinking about the Ultimatum game and how the person being offered the dollar at unfair splits has a tendency to reject the offer all together because from his perspective: To have you and your opponent walk away with nothing trumps having you walk out with little and your opponent with plenty. I would be interested to see how Spanish Fluency corresponds to Socioeconomic position in Hispanic-Americans. I would venture to guess that as Hispanics get poorer there Spanish becomes better. Semi-stereotypical but nonetheless I’d take my hypothesis to be both an indicator of one’s closeness to being first generation, or a decision to not adopt the English language in the first place. Sonia Sotomayor is mentioned in the article. It says she doesn’t speak Spanish Fluently.

http://www.npr.org/blogs/codeswitch/2013/04/29/179816884/as-americas-latino-population-grows-will-spanish-thrive-in-the-u-s

MOS

Whales in Networks

In a recent article published in Science Magazine, researchers describe a hunting technique whales have taught each other. It seems that this behavior, first observed in 1981, has spread to about 40% of the humpback whale population.

The finding is significant from a scientific perspective because it was thought that primates were the only animals that could teach each other behavior that’s not genetically programmed.

It’s relevant to our class because it seems very similar to the adoption and cascade models we studied in chapter. It’s easy to imagine that whales traveling together represent a network. From there, it’s also easy to imagine that if enough of the whales adopt the new technique, it would spread throughout the network. There’s even a good reason to think this behavior would spread from one network to another. Whales leave their mothers at age two and join other pods. If a whale was born in a pod that used that behavior and left it, it could be an initial adopter in its next pod.

Unfortunately, the original article requires a subscription to Science Magazine, which I don’t have. Here are two articles that summarize the original one. (One, Two)
This is a video that shows the technique that is spreading.