MySpace.com was at one point generally perceived as the largest and most popular social networking site, but what does that really mean for its uses for the future?

For example, its use as a learning tool. So, there are always these stories regarding both sides for social networking sites, either schools(teachers, professor, officials) are pro or against them. As to not repeat some of what others have written, the bottom line is that with technology and the future, social networking sites of some kind (maybe not necessarily MySpace.com), any kind, will from now on always exist in some form and it seems ridiculous for anyone to try to ban them completely. While I am not suggesting that educators allow their students to spend their class time on Myspace.com, it seems only natural for it to be an extension of the classroom if the students so desire. As seen in this article.

We already embrace and use tools such as Blackboard.com that is wide accept as a deliver system for our course documents. There are aspects of the tools on that site which are underused in most classes today, although that is the beauty of the customization. Each educator uses the aspects of blackboard which they will find most useful. I find at our particular institution that we under use the discussion board. I have only ever used it in one class, and it wasn’t even a class at this university. It would be nice to see what other students have asked at office hours in one location although in other ways I understand why some professors might not want that readily available to all students. What I personally see as the future of things such as blackboard.com are ways to incorporate other resources for students to learn. How many times have you been in a class and wished that there was an alternative book or online notes that you could look at. While I can understand that may undermine a professors work, they do realize that not all students will learn in the same way. Personally, I search for alternate sources for information all the time, google.com is the gateway to all other resources, and in it is my opinion that in the future, there will be classroom sites where students such as myself can post all the extra resources we have found and are using. In learning too many people are not open to the idea to exchanging information. I am not suggesting exchanging work, although that seems to be what most people think of when students use the phrase “information exchange.” What I am suggesting, are things such as the MIT OpenCourseWare where one can use other sources to enhance learning but as an integrated tool to Blackboard.com. The approach of using Myspace.com for such an addition seems troublesome. The major problem with using those type of tools is that they’re not truly made for such things and there are numerous other superfluous distracting information. Such as someone creating a Facebook group to discuss a particular class. It usually does not happen. It’s not the major function of the tool.

This brings me to my other point, how is MySpace perceived today? One could say that MySpace.com “is the Walmart of social networking sites.” This blog post on Wired.com details a person’s opinion of how MySpace is the lowest denominator of social networking sites, and it implies that it is of low information quality caliber which many people in this class may agree with. The article suggests that due to the amount of spam and content of such minimal value amounts to most people becoming frustrated and deleting their accounts. Thus they are implying that most people will use the niche networking sites for the particular aspects of Myspace.com provides. While I personally do not think that an extraordinary amount of people will leave MySpace.com I do not see it being used widespread as a tool for any “serious” goals since any interest / group / idea of a particular type will go to the niche equivalent. Example, to find a job, I would post a profile on LinkedIn since that would garner a specific type of respect, than let’s say me posting my resume on MySpace.com. Both articles suggest at the end the same thing, that we will move towards niche social networking sites to fill our needs. All of this highlights the separation of information subdivided into smaller networks (the niche networks). While it seems likely that Walmart (MySpace) will always exist, we won’t necessarily continue to shop there for all our needs.

The other day in class, Professor Kleinburg spoke briefly of Judith Kleinfeld, the psychologist at the University of Alaska, Fairbanks, who wrote a paper discrediting Stanley Milgram’s famous “six degrees of separation” findings, and his “small world problem.” To find some more information on Kleinfeld’s problem with Milgram’s famous study, I found the paper in which she attacks it. A link to it is given below:

http://www.uaf.edu/northern/big_world.html

In this paper, entitled “Could It Be a Big World After All? The ‘Six Degrees of Separation’ Myth,” Kleinfeld describes her investigation into Milgram’s famous small-world experiment as well as other similar experiments, and proposes psychological reasons why she believes the “small-world phenomenon” to be such a popular belief.

Kleinfeld identified a few reasons why she felt Milgram’s findings could be discredited; one was the first experiment conducted by Milgram, the results of which he never published. In this experiment the target was the wife of a divinity student in Cambridge, Massachusetts, and only 3 out of the 60 starter packages reached her. Also, Kleinfeld wrote that Milgram’s selection process of the “random” group of starters in both Cambridge and Nebraska was subtly biased towards the selection of wealthy people, who, she claimed, are more likely to be able to find someone through a social network. She also commented on other small-world experiments that had led researchers to conclude that it is much more difficult for paths to be found across economic (lower class to middle or upper) and racial lines of division.

Kleinfeld’s paper also discussed the psychological reasons that she believes most people so readily accept Milgram’s “small-world” conclusions. She claimed many people feel secure, believing that all mankind is connected by only a few acquaintances. She also explained that many people’s interpretation of the “small-world” phenomenon differ from Milgram’s definition; many people describe a “small-world” experience as running into an old friend or meeting a stranger who knows a friend from his or her past, whereas Milgram’s “small-world” looks at the connectedness between two random people.

 In this class I feel we have talked much more about the mathematical models as opposed to the psychological side of networks. I do not see this as necessarily a bad thing, since there is a great deal of research going on right now in using mathematics and computer science to model networks (in her paper, Kleinfeld mentions the research done by our very own Professor Jon Kleinberg), but I found this paper very interesting because it approached the “small-world phenomenon” as a psychological issue, mainly in claiming that people believe they are much more connected to each other than they really are.

http://travel.nytimes.com/2006/04/05/dining/05race.html?pagewanted=3

In Kenneth J. Arrow’s paper “What Has Economics to Say About Racial Discrimination,” he proposes that racism still exists in the workplace, though of course not to the same extent as half a century ago. This is very much true, and in the above article we are able to see such racism in the culinary world. Lance Whitney Knowling, chef and owner of Indigo Smoke in Montclair, N.J., is an experienced chef with a great resume. He recalls that five years ago he applied to an upscale restaurant in N.J., and the restaurateur was eager to hire him. However once the restaurateur found out Knowling was black, the conversation grew awkward. Though the article doesn’t explicitly say what happened after that, I think the Knowling was not hired because the according to the restaurateur, “I couldn’t have a black guy or a Latin guy back there, because it would make my customers uncomfortable.” And sometimes the insensitivity is even more blatant. Keith Williams remarks that he’s been told “The only thing you know about is fried chicken and collard greens.”

Arrow mentions in his paper that economic theories should predict that racist employers will be wiped out by non-racist employers due to the idea of competition. He admits that these market-based explanations tend to predict that racial discrimination will be eliminated, but in the real world racial discrimination is not eliminated. Therefore, other non-market factors must be involved. I found the news article to be at least remotely related to Arrow’s paper because the situation in the culinary world is a bit different from that of most other jobs. It is true that racism poses a threat to aspiring black chefs, but we cannot solely blame the employers for their reluctance to hire chefs based on color. Hiring black chefs doesn’t seem to be much of an issue for restaurants that have already had black employees. So if more of the aspiring chefs were black, this could potentially reduce racism in the future. However, this is easier said than done in this particular career. In 2006, only 85 out of 2,700 students at the Culinary Institute of America lists themselves as African-American. This small percentage is due to struggle with family members. For the most part black parents do not want their children to pursue a culinary career because since the 60’s and 70’s, kitchen work has became less attractive as other employment options arose. Therefore the scarcity of black chefs can also be attributed to disapproving family members.

However, the situation is getting better. With the boom of the cooking industry, food channel programs, and successful black chefs such as Gerry Garvin who has his own show, black parents are now less resistive. Also with the help of the scholarships given by the Careers Through Culinary Arts Program, high school students interested in culinary careers can receive the guidance and support they need to overcome barriers they may face. As Beth Setrakian, a graduate of Stanford who owns a multimillion dollar dessert industry says, “We’re on the verge of change. And thank goodness, because the heritage that we bring is a great addition to American cuisine as a whole.”

http://oracleofbacon.org/

The common game Six Degrees of Kevin Bacon is an example of the small world phenomenon.  The object of the game is to connect a given actor to Kevin Bacon through connecting movie roles in as few steps as possible, but no more than 6 steps.  The website http://oracleofbacon.org/ has several tools on it to illustrate how the almost one million actors working in the movie/TV industry in the past century can all be connected to Kevin Bacon in a surprisingly short number of steps. 

The website is an effort by the University of Virginia Computer Science department.  It works by doing calculations on the movie database provided by the Internet Movie Database (www.imdb.com).  There is defined a Bacon number which is the weighted average of all the actors in the database’s connections to Kevin Bacon.  The Bacon number is 2.960, meaning, on average, any given actor can be linked to Kevin Bacon through less than 3 movies.  The website then looks at the question of whether or not Kevin Bacon is the most linkable actor in Hollywood.  The answer is no.  In fact there are 1,048 people who are better “centers” than Kevin Bacon. 

The website has a list of the 1000 best centers in Hollywood, as well as several tools that exhibit the power of the Oracle’s searching tools.  The most interesting is found here: http://oracleofbacon.org/star_links.html.  It allows you to enter any two actors/actresses and it will display the shortest path of movie connections between them as found in the IMDB movie database.  This website certainly shows that the movie industry is an example of the small world phenomenon.

The article “Scale-Free Networks Provide a Unifying Framework for the Emergence of Cooperation” by F.D. Santos and J.M. Pacheco suggests that structure of a network influences which strategies evolve within a population. Two games one of which is familiar to our class – the prisoner’s dilemma and a variation called “the snowdrift game”- are used to examine how cooperative strategies might spread on a network.

On a large scale, network cooperation is not an evolutionarily stable equilibrium because it is vulnerable to invasion by defector strategies (R < T). The Snowdrift game is more favorable to cooperation as it removes defection as the dominant strategy. Similar to how neighbors influence an individual during diffusion of a network, this study relied on neighbors’ payoffs to determine whether an individual would switch strategies.

Previous studies found that the role of spatially structured populations (much like the ones we have been studying in class) on the emergence of cooperation varied from game to game. In contrast, this study actually found that when networks were grown using Barabasi’s preferential attachment model (described previously and in class) cooperation becomes a predominant trait for both games on both large and small networks at equilibrium independent of how the relative payoffs are set. The explanation proposed that hubs within the network are havens for cooperators. As the hubs are highly interconnected, they resist invasion by lone defectors. They found that if they removed the age-correlations that Barabasi’s model encourages then cooperation is less prevalent.

This article suggests that network structure is a necessary topic of conversation alongside whether a strategy is evolutionarily stable. I would agree as the evolutionarily stable strategy discussion harshly requires an entire population to pick one strategy that is robust against any attack. This seems to overlook some of the dynamics we discussed pertaining to information cascades and the role of clustering. If network structure influences what strategies survive, could we design networks (or the way they grow) so that over time social welfare maximizing strategies were picked over individual welfare maximizing strategies?

http://infoweb.newsbank.com/iw-search/we/InfoWeb?p_action=doc&p_topdoc=1&p_docnum=1&p_sort=YMD_date:D&p_product=AWNB&p_text_direct-0=document_id=(%2011896FD25C08D970%20)&p_docid=11896FD25C08D970&p_theme=aggregated4&p_queryname=11896FD25C08D970&f_openurl=yes&p_nbid=D62H49REMTE3Nzg5NDQ4NS42MTEwMzM6MToxMToxMjguMjUzLjAuMA&&p_multi=NYTB

This article was written a bit after the shooting at Virginia Tech, and talks about the tension in other universities and schools across the nation in the days following the attack. Many schools canceled classes in response to various threats and suspicious activities. These incidents highlight the way in which diffusion and network effects, as well as modern communications can interact in such a way that the actions of one person can have far reaching consequences.

One thing to notice is that the article doesn’t specify whether there was an increase in the number of threats against schools or whether people were just more nervous and likely to take action against responses. Chances are that it was a combination of both.  The shootings recieved a very large amount of coverage from all sources, meaning that practically everyone in the nation knew about the incident. As a result of the shooting, people who might have considered doing so but were afraid to became more likely to consider it. Others who just wanted to cause trouble might have used the shootings as a way to make their threats seem more serious. This would result in an increase in the amount of threats sent out. School officials and police, in response would be more likely to consider any threats more seriously out of fear that the threats would be more likely to be carried out. The article notes that “Most of the worries yesterday were baseless.” However, the fact that these baseless worries were taken so seriously is an example of the way in which diffusion and network effects can take a persons actions and create widespread effects.

Another interesting part of the article is the part where an official talks about how a school had to go into lockdown as a result of threat However, the direct reason for the lockdown wasn’t the school shutting down out of fear of a shooting but was a result of so many children being pulled out of school by thier parents, forcing the school officials to lock down the school.  The official called it a “roller-coaster dynamic” that resulted from “rumors circulating by e-mail and cellphones.” This rapid spread of information lead to an information cascade (”roller-coaster dynamic”) where parents reacted to the rumors and the other parents pulling out their students by pulling out their own children.

Large peer to peer networks can be very difficult to manage, and a solution developed by researchers in Cambridge is to structure the network as a social network. Their inspiration was the way in which information (gossip) travels person to person through a group of people. A large network modeled this way means that each person is only connected to a few other peers, instead of everyone in the network. With networks consisting of thousands of members, structuring a network this way has proven to be much more efficient.

http://news.bbc.co.uk/2/hi/science/nature/1939928.stm

“Building the Infinite Internet” by Scott Woolley, April 23, 2007

http://www.forbes.com/free_forbes/2007/0423/068.html

As the internet continues to grow in size, there is a greater and greater need to find efficient ways to transfer data between servers and computers. According to the article, Akamai Technologies Inc. provides methods to overcome some of the archaic rules of the internet to accommodate the need for speed with increasingly larger demand on the network. The article comments on three typical problems the internet may encounter that Akamai claims to solve (in the sidebar “A More Clever Internet”).

1. Flash Crowds: A large amount of users from all around the world try to access the same site or file, swamping the server that holds this data.

2. Fat File Paradox: With the increasing use of the internet to transfer very large files such as movies, a large amount of time is wasted on confirmation messages between computers after sending only 128,000 bits.

3. Line Cuts: When certain internet lines fail or are cut (such as when undersea cables snapped due to the recent tsunami), files get lost and it takes awhile for internet servers to find new paths to other computers.

Akamai’s solution to all three of these problems is to provide a shorter path then already available on the internet. The picture below shows the concept used:

In essence, Akamai servers monitor their clients’ websites and determine how data could travel more efficiently. They do this by creating a new shortest path in the network. For example, in the case of the flash crowd problem, if the Akamai servers determine that there is a high demand for a certain picture in New York City from a website they serve in Los Angeles, they will copy the picture and store it in a server located near New York City. Therefore, all users in New York City were provided a new shorter path to the information they demand. In this way, traffic build up is avoided and information travels a shorter path to the users. This technique basically tries to find and create shorter paths on the internet in real-time, to meet the current demands on internet.

We talked in class about Google Trends, and touched on the idea that Google was increasingly using information collected from users as they searched to improve its engine. It appears that these two things actually go hand in hand, and that Google trends itself is useful user data, although not in the conventional sense.

The way user data is typically used by a search engine involves watching what links people click when they search for a certain query. As a simple example, if everyone who googles ‘stewart’ clicks the fifth link, that’s an indication that the fifth link should be moved up. Conversely, if people googling ‘OED’ don’t click any links, but then immediately search for ‘Oxford English Dictionary,’ that tells us something about what they were looking for.

Google Trends is user data too, in a different sense. Just seeing the popularity of various search terms isn’t terribly helpful to a search engine, unless it can somehow predict when those terms become popular, as in the case of annual holidays and so forth. But the ability to compare, and correlate, different search terms is tremendously powerful.

As an example, look at this. We see a few interesting features of this graph. First, whenever there is a spike in searches for “Barack Obama” there is a corresponding spike in searches for “Obama.” The graphs are incredibly well correlated. Furthermore, as time goes on, searches for just the last name “Obama” become more prevalent than searches for his full name. Note that the graphs still follow each other quite nicely. Finally, almost nobody searches for just the word “Barack.”

There are several conclusions we can draw from this. First, when people search for “Obama” they almost certainly mean the Democratic Senator from Illinois. Whenever there is a jump in searches for one, due probably to a news story or other real world event, the other follows suit. Additionally, Barack Obama has become increasingly associated with just his last name: whether as a result of increased name recognition, or just the perception among users of increased name recognition, more people look for him using just his last name. As a corollary, almost no one identifies him by just his first name, either because they know the query won’t be understood, or because it’s simply more conventional to identify politicians by their last name.

In effect, we can use Google Trends to connect ‘nickname’ searches with a more specific proper name. This pattern is borne out by many other queries, although it’s perhaps easiest to observe in famous people. There are counter examples: Martha Stewart is not strongly correlated with either her first or last name, because they are not ‘nicknames’ for her. On the other end of the spectrum, Cornell is so strongly identified by its ‘nickname’ that there is basically no connection between the search trends for “Cornell” and “Cornell University.”

Given the vast amount of data and processing power at Google’s disposal, it’s possible that these trends could be added to their new feedback powered engine in the future.

An information cascade occurs when individuals adopt a new behavior based on the signals and actions of individuals surrounding them. We can also treat this propagation of a new behavior throughout a network as games played between individuals in which the superior strategy is “passed down” to individuals in the “outer levels” of the network. In biology this idea is known as natural selection and sometimes as “survival of the fittest”. Crediting the biological origin of this idea, this branch of game theory is called evolutionary game theory and is more concerned with how a new behavior possessed by a minority may affect the whole population.

In “Survival of the Clearest”, Steven Pinker talks about evolutionary linguistics and how evolutionary game theory models defining properties of human languages. In the evolutionary game theory paradigm the “behavior” that is propagating through the network is a particular type of language. In the model, we assume that a better language enabled our human ancestors to survive longer and allowed them to produce offspring that inherited these communication skills as well. James Hurford used evolutionary game theory to show that arbitrary bidirectional sign is evolutionary stable in 1989. Arbitrary bidirectional sign describes a community in which they implicitly agree on certain signals to refer to particular concepts.

One of the problems with this scheme is that there are more concepts in the world than the number of unique sounds humans can produce for each one. At some point it will become difficult to distinguish the sounds correctly, and impede communication instead of facilitating it. In 1999 Nowak and Krakauer showed that organisms never transmit information perfectly partly for this reason. They showed one way to overcome the limitation is to limit the number of sounds, but string individual sounds together to express different concepts, which we call words. With so many words it’s highly unlikely that all of them will “survive” unless people continue to use them. Nowak et al showed that this wasn’t a limitation if people related words to components of an event (e.g. from article is dog bites man), thus gradually the language develops syntax and semantics. Although this is a model of how language may have evolved, Pinker points out that game theorists continue to show evolving nature of many special features of language such as arbitrary signs and duality of patterning. As more abstract elements of language including lexicon, phonology, syntax, and semantics are shown to be the result of physical limitations some suggest that the evolution of language is closely related to human evolution.