Microsoft has an interesting project that they are presenting at the International Conference on Weblogs and Social Media, which is occurring right now (Microsoft’s project will be presented this Wednesday). Blews is a project that hopes to show what the political blogosphere tells us about news. Its goal is to move a step beyond typical news-aggregation sites, which usually sort news by categories, by identifying which news stories are the most frequently discussed political topics (user ays26 recently discussed Google News, a great example of a typical news-aggregation site). The argument is that the most frequently discussed story should be the most important story in politics, and therefore the most interesting story to the user. Blews shows the user the number of liberal and conservative blogs that link to a particular story, in addition to the level of emotional charge of the blogs. Another benefit of Blews is that it “enabl[es] a reader to compare different views on the same story from different sides of the political spectrum.”

In class, we discussed the link analysis ideas of hub-authority and PageRank that are used in the ranking functions of search engines. Blews appears to use similar link analysis methods to help determine the most important political story. In this way, Blews functions more like a standard search engine than typical news-aggregation sites, which rely on sorting news stories into topics. While the basic link analysis may be similar to a search engine, Blews limits itself to a very specific set of pages that link to news stories: political blogs. Also, Blews uses the textual content of each blog to determine its emotional charge, which I assume it uses to help weight the importance of that blog’s links. In other words, the higher the emotional charge of the blog, the greater likelihood that the story it links to is interesting. The news story with the most highly emotionally charged links is the most popular.

The idea of Blews is a novel one, in that it uses a select group of people to determine the most interesting story in politics. It appears to be a proof of concept, but I’m sure that more link analysis ideas will be incorporated into news-aggregation websites in the future.

This academic paper, “Oxytocin Increases Generosity in Humans,” details the study of the effect on material generosity from greater-than-normal doses of a hormone in a small sample of test subjects. The game used during the experiment is a variation of the money-splitting game we considered as part of our exploration of network exchange theory.

In the study, Paul Zak of Claremont Graduate University started with 68 male participants (women were not included since increased doses of oxytocin raise the risk of miscarriage) and gave half of them oxytocin (OT) by nasal inhaler. The other half were given a saline solution as a placebo. Paired randomly, each subject was identified only by a number and separated from his partner (no talking was allowed). In the first trial, one of each pair of each pair received $10 and was required to offer a portion to his partner. If the partner accepted, they would divide and keep the money. If the second partner rejected the offer, they would both walk away empty-handed. Before learning what role he would play, each subject was asked about his preferred actions for both positions. This made each put himself in his partner’s shoes before beginning. In the second trial, the same partners were paired; however, this time, the second subject had to accept what he was offered. All players knew the nature of the game and were playing for real cash.

The OT had no effect on the minimum offer a subject was willing to accept for either trial–it was $2.97 on average, regardless of OT or placebo. However, when it came to giving, the OT made a significant difference. During the first trial, those who inhaled OT offered an average of $4.86, while those who received saline offered an average of $4.03. When recipients had to accept the offer regardless of their personal preference, in the second trial, offers were $3.68 on average with little difference between OT and placebo users. We see that giving is reduced when the giver does not explicitly consider the receiver’s reaction.

This is interesting to consider for a number of reasons. First, it highlights the way in which unconscious biological processes (ie, the release of hormones) or the simulation of such (eg, inhaling the hormone) can lead to altered social behavior. Second, it is interesting that the receiving subject would sometimes refuse the offer. We discussed this possibility when working out the balance of power and end-results with the money-splitting game was played with different nodal configurations. Third, we can see the demonstration of power in this small, two-person network during the second trial, when reject was removed as a choice. Since the receiver had no other options, the giver was in a more powerful position than before.

It is worth pointing out that Zak recalls mice without OT receptors exhibit signs of social amnesia, lacking social memory and engaging in atypical social behavioral patterns. Zak said in an interview with Discover Magazine, “All kinds of daily transactions require that people spend just a little bit of their time and resources to help someone out. I think society as we know it couldn’t exist without that.” Indeed, he may be correct, as figures for charitable giving continue to rise and philanthropic foundations have an increasing impact on the world. Some see the current trend in giving, especially by the super-empowered wealthy and visible elite like Bill Gates, Larry Page, and Sergey Brin, as the beginning of a cascade of contributions. We can only hope that the prosperous among us respond either to the signals they are receiving or the actions of their peers in a way that leaves us all better off.

Note: I originally came across news of this paper while reading the “Raw Data” section (entitled “The Generosity Hormone” by Jennifer Barone) from Discover Magazine’s April 2008 issue.

http://www.nytimes.com/2008/03/30/business/30fund.html?ref=yourmoney

As of now, the news of Bear Stearns has become widespread. With company stock valued at merely $10, Bear employees who had invested one-third of the company stock lost a majority of their personal wealth. Similar to the case of Enron, the collapse of the company also shattered the personal wealth of employees who held so many shares. To this day, it has been demonstrated that many employees are still investing too much in a single stock especially that of their own employer. It is recommended that one “invests no more than 5 percent in employer stock. This is especially true for employees of a large company whose stock is widely held, because they may already own some of its stock indirectly.” Thus, the fact that at least 40% of 401k participants are making huge bets on their company stock with numbers over 20 percent is extremely significant in terms of its implications.

Defined as a situation in which people observe the actions of previous deciders and make the same choice ignoring the information sent to them by their own private signal, information cascades are demonstrated. As employees of Bear Stearns, individuals were shown to invest heavily in the company’s stock even though the previous Enron example showed the disastrous outcome of doing so. However, it is important to note that unlike Bear Stearns, Enron was a company that encouraged employees to invest in their 401(k)’s with company stock. Bear Stearns, however, as one of the previously top ten investment banks where money and investing is their business, can now serve as a source of public signal that may well overturn this information cascade, motivating employees to diversify their holdings (accepting or rejecting alternatives). In addition to the Enron incident, these two signals have provided more information and value for future employees to analyze and if such a public signal is rejected, such a cascade may not be overturned.

Apparently in the United States alone, there are around 20 million stamp collectors — it’s one of the most popular hobbies in the world. It makes sense; the rarest of stamps have sold for amounts on the order of millions of dollars, and less rare stamps can sell for tens of thousands. Clearly, stamp collecting is an investment.

However, The Independent details a time where the investment potential of stamps became so well known and pursued that the market itself collapsed:

But 20 years ago stamp prices did rocket out of control. In the late 1970s, a few unscrupulous individuals started to talk up the investment potential of stamps. Lots of articles appeared about the rise in the value of stamps, and national newspaper advertisements were taken out. Interest in philately as an investment medium gathered, as did momentum in prices. By 1980, average prices had jumped eight-fold. But a year later the market had been blown up out of proportion; the bubble burst.

This is clearly a case of an information cascade. As soon as people started seeing others notice the investment potential of stamps, they themselves began to take notice, apparently regardless of how safe of an investment it actually was. Unfortunately in this case, the information cascade took a turn for the worse since the huge number of people attracted to the hobby actually caused the market to collapse, or the bubble to burst — a case of a network effect.

Of course, this is not a unique incident. Bubbles have burst before — the internet bubble of the 90s and even the case of Beanie Babies, mentioned previously on this blog, are examples of the same type of phenomena.

What scares me most about information cascades is our society’s complete reliance on what we hear. Like one of our childhood rumors we let the decisions of others guide us almost blindly and take what is said for granted without a second thought. As I think about some of the products that have recently been released I can’t help but wonder how much of their success was due to information cascades and whether or not the success (or failure for that matter) is justifiable.

The battle between Blu-Ray and HD DVD illustrates perfectly what I mean. While the battle is essentially over now, when asked in the past I would always throw my support towards Blu-Ray. If asked why I felt that way I could rattle off a list of facts and figures and would most likely comment on the better quality relative to cost. Yet in actuality I am completely uneducated about these products. I have admittedly not seen anything on Blu-Ray nor have I ever seen anything on HD DVD, and I can’t really say anything about quality relative to cost with any certainty. What’s more, I am certain that I have influenced at least five individuals to purchase Blu-Ray products on these false bases.

The release of Microsoft Windows Vista is another perfect example, only in this case I actually do have some experience with the product. Prior to every using Vista I was told by numerous people that it was slow and it crashed often. Some even went so far as to joke about how they had Vista and they were upgrading to Windows XP. So I found myself thinking that if this is the general consensus then it must be true, and today I am hesitant to purchase a new computer that runs Vista. It’s not that simple of course, because my specific observations contradict what everyone has been telling me. I have had the opportunity to use Vista on several occasions, and have yet to have any problems with crashing or slowdown. In fact I have been more than satisfied with the product. And yet, I am still hesitant to buy it because of the large opposition. As far as I am concerned there must be something wrong with it that I am just not seeing.

Looking back, I have begun to think about all of the products I have ever purchased and how many of them I purchased based on my own information (not many). I can only imagine that most people are like me and don’t conduct much of their own research when looking into new products. And if no one is doing any research, then the value of information cascades is useless. Regardless of whether the group consensus is right or wrong, information cascades are not a substitute for personal research, yet in our society this seems to be the norm.

The idea of information cascades influencing new product releases can be found all over the web from the release of Vista to new movies in the box office. Below are just some of these articles:

Information Cascades, Randomness, and the Movie Business by Paul Kedrosky

Information Cascades in the Adoption of New Technology by Eric Walden and Glenn Browne

Code Igniter vs. Cake PHP by Joe Rosenblum

http://blogoscoped.com/archive/2006-07-28-n49.html

In class we discussed PageRank and the hub-authority computations that allow webpage owners to manipulate their placement in Google search results.  This is useful for most webpages, but what about news sites that want their stories to appear on Google News? Google’s methods for ranking which articles appear on the Google News homepage are different than their regular search results, so it requires a different approach.

Google News does not crawl the web looking for news articles the way regular Google search does.  It uses the opt-in method that search engines used before web crawlers came about.  This gives Google some human screening abilities to make sure that your site is a credible news source.  Once your site is accepted into Google News, you supply a page that contains an up-to-date list of links to all of your current stories and the Google News scanner checks it for updates every few minutes.  New articles appear on Google News within minutes. Since all the news sources are pre-screened, they are all “Authorities,” so running a hub-authority computation on them is not going to help so much.

One important difference between Google News and regular Google search is that Google News clusters articles by topic.  (How they do this is still a mystery, but it probably involves connected components and graph clustering algorithms, in addition to many other interesting networks problems.)  On the homepage it only shows a few stories from each cluster.  Logically, it would seem that the way to make your article appear more often and not get lost in the cluster is to make your article sufficiently unique that it won’t be clustered.  Google thought of that, however, and realized that most of their readers are not so likely to be interested in stories that only one of their 4500+ news outlets reports on.  Rather, they concluded that the most interesting stories will be found in the largest clusters.  So clearly, writing obscure articles and making yourself an outlier is not a dominant strategy.  A dominant strategy would certainly be to write articles that fit into the largest cluster, but the question is how to get yourself up to the top of the cluster and not lost under the “All 2,917 news articles” link.

Of course, given the nature of news, it would not be in Google’s interest to leave any single article as a headline for too long, since people want the “latest news,” not something from a few days ago, or sometimes even a few hours ago.  Often the headline article on Google News changes every 15 minutes or less.  The only method that seems to guarantee you a good place in the cluster, at least temporarily, is to beat everyone else to the market.  Google News rewards articles that break the news first, so for a while, if you are the first to report a story and your cluster becomes sufficiently large to bring your story to the front page, you are basically guaranteed the headline, regardless of any other ranking criteria.  After the first 15 minutes, though,it becomes anyone’s game. Certainly, if you publish multiple articles on a story that make it into the same cluster, your chances of making the top 3 in the cluster become higher, but Google must have a better way of deciding.

While Google hasn’t released their methods to the public (that I know of), I’d like to hazard a guess as to the method they might use.  One possibility is a variation on the hub-authority computation.  With each successive story that a news source publishes, Google learns something about the nature of the news source based on what clusters its articles end up in.  It might be anything from it being a local vs. national vs. international source, to specific specializations in different types of news, to whether the news source frequently publishes press releases and AP content or actually generates unique articles. This information would contribute to an authority score in each of these areas.  Google can then parse all of the articles in a cluster to decide based on some predefined criteria what authorities are needed to make a good article in this cluster.  The cluster is basically functioning as a dynamic hub.  Since articles are constantly coming out (Google News claims they index 100,000 articles a day), this algorithm can be run and the scores can be updated more or less continuously. This, combined with some weighting for how recently the article was published would generate a pretty good result. So basically, in this situation, Google would function as its own hub for the hub-authority algorithm.

In class we talked about different applications of Information Cascades, one of which was best-selling books. The music industry is a similar application. There is a best-sellers list for music, and being on the best-sellers list obviously helps musicians when they’re selling albums and when radio stations are choosing which songs to play. But today listening to music is a lot different from reading a book. You can read reviews about books, maybe read summaries or flip through a few pages. But when it comes down to it you get very little information about a book before you buy it, and your best source of information is really other people’s actions. But most people have heard an entire song on the radio before they go to buy an album. Even if they havent, most songs are available online to stream for free, and a lot of stores (I havent been shopping in a while, but I know at least barnes and noble does) have a way to let you preview each song on a CD. So there’s actually quite a good deal of information that someone can get about a CD before making a purchase, there’s no reason to believe that the music industry would behave like the books.

http://www.nytimes.com/2007/04/15/magazine/15wwlnidealab.t.html?_r=4&ref=magazine&pagewanted=all&oref=slogin&oref=slogin&oref=slogin&oref=slogin

This article, however, discusses how success in the music industry is rarely related to talent or even how good the music is. While, of course, many musicians are very talented, I think the point of the article is that there is not a strong correlation between success and talent. Producers seem to have an impossible time predicting which musicians will become stars and which ones wont make it very far, no matter how much experience they have. They say it comes down to being popular at the right time, and that success follows a “rich get richer” pattern. Much like information cascades, when artists get off on a good start, they tend to be more successful as buyers tend to buy what’s popular.

What the article said that was most interesting was that buyers tend to follow this pattern even when they dont have to actually buy anything. The writers did an experiment where they created many different “universes,” and in each universe ran a survey. Each subject listened to a collection of 48 songs and chose their favorites. In some universes the subjects were allowed to see previous results. And what came out of this was that when buyers were able to see past choices, they tended to pick the same favorites. When they couldnt, the favorites were more evenly distributed. Also, the example cited in the article states that in one universe, the song that ranked 26 overall became the number one hit because the first couple subjects happened to like it best. What’s most interesting about this is that the subjects actually thought they liked the songs better when other people liked the songs. It doesnt seem like anyone else should have any ability (especially someone random) to tell what kind of music you like, but people fell into cascades anyway.

http://www.npr.org/templates/story/story.php?storyId=88030744

With Hillary Clinton refusing to drop out of the race and neither candidate looking likely to score the 2024 delegates needed to ensure the Democratic party’s presidential nomination, its looking more and more likely that the eventual nominee will be decided by a vote of the 794 super-delegates at the party’s August convention in Denver. These individuals have no formal obligation to vote in accordance with primary results in their particular state/district and can thus vote freely for the candidate of their choice. In some respects, the voting decisions of the super delegates and actions of the two candidates incorporate elements of game theory and strategic behavior. The link above is an NPR radio segment and text summary of an interview with game theory expert Jim Miller, a professor at Smith College, discussing some potential game theoretic political strategies and implications.

Of particular interest and relevance was the discussion of the voting motivations of the super delegates. Jim Miller suggests that instead of voting in the party’s best interest, some will no doubt instead weigh the potential rewards and punishments involved with choosing or not choosing one candidate over the other and thus vote to maximize their individual benefit. In this sense, to reduce the severity of negative political consequences, super delegates may be tempted to vote for the candidate perceived as being more vindictive; Hillary Clinton. While this sort of scenario might be difficult to represent as a simple game, it can be thought of as one and the strategy of voting for the tougher candidate to minimize possible personal fallout could be characterized as a maximin strategy.

Another possible interpretation of the race between Hillary Clinton and Barack Obama is that they are competing against each other in a game where the payoffs are super delegates. Strategies and responses could be considered to be things like Clinton’s remarks about how Obama would make a good vice president, which have been seen as attempts to discredit the viability of his candidacy and sway super delegates to her side. Interestingly, Miller suggests that Obama best response to these offers would be to flat out reject them and the notion of a vice presidential bid, which he has since done. Similar sorts of delegate-persuading tactics on Obama’s part would include promoting the idea that he run on a third party ticket if not given the Democratic nomination and suggesting before the vote like he has been currently that any outcome in which the candidate with the most regular delegates and popular votes doesn’t receive the nomination would be tainted and illegitimate.

http://kin.naver.com/detail/detail.php?

d1id=4&dir_id=41401&eid=71p5mUmScjd/oD3X+r/21KICI/GAs/6i&qb=aW5mb3JtYXRpb24gY2FzY2FkZQ==

This link leads to a page that talks about what an information cascade is, and how the Internet is related to the phenomenon.

An information cascade occurs when there so much information that you cannot make a decision just by the signal you get. Instead, you have to look at the signals that others have received before you did and decide based upon their choices. For instance, let there be two bags: one has two black stones and a white stone, and the other has two white stones and a black stone. After taking out a stone from either bag, you have to decide which bag has two black stones and which bag has two white stones. If you were the only one to try this, then you would decide based on which stone color you get. However, if there were many people who have tried this before you did and many of them have taken out a black stone, then even if you get a white stone from the same bag, you would decide that the bag has two black stones.

Although an information cascade occurs due to logical thinking, it can lead to false results. The Internet has been there to prevent us from making bad decisions. For example, by searching through the Internet, we can find authoritative information about certain topics, objects, and ideas and make decisions of our own based on the signals we get.

However, as time passes, the information we can get from the Internet increases, and the number of Internet users increases. As a result, the Internet is increasingly becoming a source of information cascade nowadays. For instance, on youtubes or other sites, users can leave comments, vote on comments, and rate videoclips. Although you cannot get the definite number of total users or the order of usage, you can practically get the information on what previous users have decided on the information. As a result, if a videoclip has a high rating, and a pro-comment has many votes, even if you don’t like the videoclip, you would decide that perhaps it is a good one.

Can rumors bring about the demise of a venerated Wall Street investment bank? According to the Wall Street Journal, the Securities and Exchange Commission is currently looking into whether market rumors contributed to the downfall of Bear Stearns.

“Bear Stearns has been subject to a significant amount rumor and innuendo over the past week,” said Alan Schwartz, CEO of the firm. “Rumors intensified and given the nervousness in the market a lot of people it seemed wanted to act to protect themselves from the possibility of rumors being true and didn’t want to wait to see the facts.”

With the sub-prime mortgage crisis and talks of possible U.S. recession in the air, rumors regarding trouble at Bear Stearns began to spread in the market: the Fed was about to step in to help Bear manage a liquidity crisis. One by one, worried traders started to sell off stocks and everyone else started to do the same. Bear’s executives refuted rumors about the company’s liquidity squeeze, but it was too late. As the market began to lose confidence, panicked investors pulled funds and lenders cut off credit to the Wall Street bank. Price took a steep fall all the way from last year’s $170 per share to a mere $2 per share buyout offer from J.P. Morgan Chase, which totals up to $240 million. Apparently, JP Morgan Chase has decided that the Bear Stearns is only worth one sixth of the $1.5 billion Manhattan headquarter building, which is included in the buyout deal.

“One of Bears’ key mistakes may have been to ignore the rumors for too long. By the time the CEO appeared on TV, it was too little, too late,” writes Marketing Pilgrim’s Andy Beal. “When companies don’t come clean, it’s guilt by omission. In the absence of credible information, investors will fill that void with their own best guesses and follow the wisdom of crowds.” Information that each person infers from other shareholders’ choices overwhelmed the private information at hand.

Bear’s stock, however for some strange reason, never actually hit $2 per share bottom but jumped from $3 and hovered around $7 for awhile, leading more people into confusion. Herding behavior is also observed here because people, surrounded by uncertainty, are just watching how everyone else reacts. Everyone is thinking “something’s up.” Many investors came up with different theories and speculations on why the share is still hanging in there. Recently, J.P. Morgan raised the bid to $10 in order to calm angry Bear Stearns shareholders and close the deal.

Confidence seems to play a big role in how well the Wall Street banks perform. Once bad rumors of huge losses surface, the firm falls into trouble because everyone pulls their money away, making it worse and worse. Christopher Cox, the Securities and Exchange Commission Chairman, said the collapse of Bear Stearns was due to a lack of confidence, not a lack of capital. Cox noted that Bear Stearns’s problems escalated when rumors spread about its liquidity crisis which in turn eroded investor confidence in the firm.

Sources:

http://blogs.wsj.com/marketbeat/2008/03/20/hints-and-allegations-and-bear-stearns/

http://www.marketingpilgrim.com/2008/03/bear-stearns-a-lesson-in-rumor-monitoring.html

http://www.businessweek.com/bwdaily/dnflash/content/mar2008/db20080318_327039.htm?chan=rss_topStories_ssi_5

http://www.foxbusiness.com/markets/industries/finance/article/secs-cox-says-bear-collapse-crisis-confidence_529965_9.html

http://blogs.wsj.com/marketbeat/2008/03/14/the-bear-stearns-conference-call/