Over the summer, I worked at a company called Campus Promotions, part of Student Agencies Inc, that does marketing and consulting for local companies. One of our big projects is the Ithaca Gorge Dining Guide which is a guide to local restaurants. This was the first year ever we came out with both a print and digital publication. After extensive market research about competing websites, I worked along with our Tech Analyst and used Squarespace.com, a developer platform created by Google, to build our new website – gorgedining.com. The website is intended to be a student-view into dining in Ithaca. Since we sell space in the print booklet and the website, we want our new website to get as many views as possible, and therefore a high ROI for our customers.
Having little marketing or web design experience, I was struggling to figure out how to drive more traffic through the website, when we came to Chapter 14. Chapter 14 discusses how websites are linked to one another and introduces the ide of PageRank. PageRank is like a fluid that settles into a network, passing from one node to another based off of links as edges. A website passes its share of PageRank onto any nodes that it connects to. So, the more nodes a page is connected to, the more PageRank it receives. This seems to explain the intuitive – the more websites that direct people to your page, the more views you get, and the higher your PageRank climbs.
This all, in theory, makes sense: if you link to more pages, you will get more views. But later in the chapter, they introduce the concept of SEO – Search Engine Optimization. Search Engine Optimization uses strategic tactics to improve the search engine performance of a website. The large search engines are constantly maneuvering and changing their PageRank and scoring systems to prevent Web designers from taking advantage of the system.
With these two factors in mind, I looked into what I could do with GorgeDining.com. First, I linked it to a few relevant external pages; the Student Agencies Website, and Facebook. Then, on November 2nd, I posted a blog entry and linked it in the Cornell 2017 class group on Facebook). This was strategic because that was Freshman Parent’s weekend – a prime opportunity for restaurants.
I saw an immediate spike in views, and was able to use Squarespace’s analytics to discern where the references were coming from.
Blog 2 graphics - Click to see the page view and source data
Then I looked into SEO with Squarespace. Squarespace is a Google product, so I figured they’d have some insight into SEO’s best practices. I was not surprised to find out that all Squarespace websites are built with cutting edge SEO adaptations. One I found particularly interesting was their rel=canonical meta tag. What this means is that if there are multiple variations on a link or internal pages (for example when you click on one of the restaurant internal pages on Gorgedining.com), Squarespace will automatically index the URL’s that should be used when there are variations. So, instead of each of the pages within my website being ranked separately, they can all come up under the search for any variation of the gorgedining.com URL. That way, they can all share page rank and search hits, instead of standing alone.
When I have a bit more free time, I think the next move will be to post links on popular review sites like UrbanSpoon and Yelp! and also to reach out to the restaurants we work with and ask them to post links to GorgeDining,com on their own websites. We are also looking for a food blogger to generate fresh content. If you have any suggestions as to how we can drive more traffic through the site, or want in on the project, shoot me an email– firstname.lastname@example.org!
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The ability to learn from peers gave the human species a distinct advantage evolutionarily. Even in modern times, this tendency to follow others can be seen in Information cascades (Chapter 16). Information cascades occur when others’ decisions affect the decision of another person to the extent where they follow what others do regardless of their own personal signals.
An interesting property of information cascades is that some people have more personal signals available to them. On a similar note, some people believe that others have more signals and follow their decisions more. This is related to what happens in marketing and advertising. Often times, big companies sponsor athletes and give them monetary compensation in exchange for the athlete using the product. For example, one article , talks about how this sort of sponsorship leads the customers to believe that the brand supports the athlete and the athlete vice versa supports the brand. Due to this, future customers who are fans of a certain athlete are more willing to buy the sponsoring product because they think the athlete using it and thus, the athlete’s personal signals trump or add to add to any personal signals. The athlete essentially acts as a peer with many signals that affect the decision of a customer. Thus, through sponsorship, customers become more likely to buy a sponsoring product. As more people buy the product, or as the product sponsors more people, an information cascade develops that act to trump any negative personal signals or add to any positive personal signals.
Another interesting study , showed that companies were becoming event sponsors in order to target market at least 54% of the time. Target marketing is essentially where companies sponsor in order to attract a target audience who are likely to buy their product or a similar product. Again, through the sponsorship and information cascade begins whereby future customers use sponsorship as signs of positive signals from others and thus become more likely to buy the product. This not only shows the power of information cascades, but also shows that information cascades exist in very significant parts of our society.
The PlayStation 4 has just been released, and amidst booming initial sales and hype, reviews
have been mixed. The PlayStation 4 has taken the first punch in what will surely develop into the new generation console wars. The PlayStation 4 hopes to ride its momentum in its hope to knock the Xbox One off of the market, but was Sony’s decision to release first the best option? Are there advantages to Microsoft waiting? Both of these questions can be analyzed from a networks perspective. By utilizing the concept of information cascades, we can take a more in depth look of how these two products compete and what it means for their future success and strategy.
As the author Erik Kain mentions, PS4 has not been getting the most favorable reviews both in terms of hardware–there are some hardware defects which people have been receiving–and its less than thrilling first-party launch titles. Kain also posits the question “But what happens if the Xbox One lands with generally more favorable reviews than the PlayStation 4? What happens if the Xbox One game lineup receives higher praise?” This type of question plays into the concept of information cascades. When people are trying to make decisions about what products to buy, they not only consult their own intuition, but also look to the internet and reviews as a source of information. Since the PS4 has been having technical difficulties and a lack of good software, people have been reviewing the PS4 negatively. This could be a potentially bad situation for Sony. When people have access to other people’s opinions on a product, then (as we learned) that information gets considered by those who read the reviews. Then based on a combination of their own opinion and the number of signals they get they will either purchase or abstain from purchasing the product. Since Sony has had a large number of initial customers, there is plenty of reviews and information available for the next wave of consumers. This information then will affect their decisions and may shift the balance of power to Microsoft.
Thus, PS4′s early release allows for more information to be collected by consumers before the launch of Xbox One. We will have to wait and see how this affects the sales of Xbox, but from a networks perspective, we can make the prediction that people might shift in long term towards Xbox due to the lackluster launch. Of course this is a simple prediction which does not take into account a lot of factors, but it is something that definitely might define how the console wars pan out.
Information Cascades (Chapter 16) occur when people observe the actions of others and then make the same choice as others have made independent of their own information signals. This occurs mainly due to two reasons: the fact other peoples’ behavior can convey information about what they know and observing this behavior can be rational sometimes. Secondly, the fact that there is some kind of direct benefit when you follow someone else. Information cascades occur in various real life situations like politics, marketing, social networks etc. But how fast do these cascades actually help disseminate information to the crowds?
In this paper, researchers bring out an interesting point that sometimes information cascades do not occur as quickly as one might expect. They take the popular social network, Flickr and analyze the factors due to which information cascades are delayed. Particularly they investigate two factors that might have caused significant delay:
1. Bursty login times: Because users need to login to browse photos they have a window of time (login session) to receive content from their neighbors. Therefore, this factor directly contributes to the delay in information propagation
2. Content aging: As new photos are uploaded the availability of a photo from a particular user diminishes. As a result, additional clicks are required to access old photos which further delays the ability of photos (in this case old photos) to spread.
These two factors impose a crucial constraint on information propagation as the user has to not only be active but the content from his friend circle should be available for him during that time period. As a result of this, information takes a long time to propagate through the social link which means that popularity of content usually remains steady over time. Users are unable to imitate other’s behavior as they rarely get input. On a higher level this means that it usually takes long time to obtain an aggregate population outcome in Flickr.
What does this mean to us? This is a good example of the fact that cascades can be fragile and based on very little information. Since users are only logged in for a window of time which limits input from others their decision can be often based on very little information that gets passed on. Similarly as new photos get uploaded cascades from previous photos stop which creates a further delay. Therefore, although information cascades in various other markets such as the buying market have a tendency to spread quickly, in Flickr and other social networking websites with similar behavior they may actually experience a delay.
A Takeover Bid for BlackBerry Collapses, and Its Chief Executive Vacates His Post
One of the formerly biggest players in the mobile phone industry, BlackBerry is currently in dire straits. Indeed, right now it has very little competitive advantage in both the mobile industry, in which Android and iPhone are dominant, and the new software and services industry it is trying to enter, in which other companies already have established and successful software that allow corporations or governments to control their employee’s handsets. As a result of its uncertain future, a recent takeover bid for BlackBerry has failed, and even its CEO has stepped down. In many ways, this almost dramatic decline of BlackBerry can be attributed to many of the concepts learned in class.
When purchasing technology such as a smartphone, there is a wealth of reviews and information on which phone has the highest specs, is most cost-effective, etc. Although people do not precisely buy a cellphone solely based on the signal of the person who bought before them, but the signals of a few cellphone reviewers can have an incredible information cascading effect on buyers. The top few reviews that come up when searched will have a significant influence on consumers, and these consumers will send signals to other potential consumers, causing an information cascade. In the case of BlackBerry, mediocre reviews coupled with high reviews of other smartphones can be attributed as a factor in its decline. Furthermore, the direct benefit principles cover in class also apply. As BlackBerry’s market share gradually decreased, it eventually passed its unstable equilibrium, and BlackBerry’s supposed popularity became less than its actual popularity, causing people to deviate away from BlackBerry as less and less people use. By direct benefit principles, the BlackBerry is tending to the stable equilibrium of 0, which is roughly what is happening as BlackBerry is more or less leaving the cellphone industry and entering the software/services industry, as talked about in the article. Ultimately, the principles of Networks have far reaching effects into our daily lives, and this is one example of such.
In the article, The Network Effect, Julie Driscoll talks about what the network effect is and how it can be utilized by technology companies to maximize investments. Driscoll defines the network effect as being the “impact that one user of a good or service has on the value of that product to other people.” The first step in capitalizing on the network effect is to work with engineering and product design teams to collaborate better with sourcing teams. The engineering and product design teams create CAD designs of the product and send CAD drawings to the sourcing teams in order to get the product manufactured. In order to promote better collaboration, Driscoll recommends that all members of the team should focus on product cost in order to maximize overall savings.
There are suggestions provided for all of the different roles including the design engineer, the manufacturing engineer, and the project manager. The design engineer usually designs for form, fit, and function, but they can also design for costs if the program manager gives them a target cost. The project managers can help out by finding catalog parts instead of creating custom parts as well as carrying over old parts to use in the new designs. Manufacturing engineers can work with the design engineers in order to see whether outsourcing certain parts could save the company money.
The next step for increasing the utility of the network effect is utilizing enterprise automation solutions which allow businesses to communicate with their suppliers more directly. Companies traditionally would send printed CAD drawings to suppliers in order to get parts made. With the enterprise solutions, companies would be networked with their suppliers who would be able to simply open up the CAD model saving a lot of time. Instead of sending printed drawings back and forth, suppliers and engineers could work together on the model simultaneously to reduce costs.
This article relates to Chapter 17: Network Effects from class. In class, we looked at the network effect and how people can benefit from following each other in buying products such as a fax machine, using online services like Facebook, and choosing a restaurant based on the number of people inside. This article describes how the same effect can be used when creating technology products to minimize costs and maximize profits. Aligning all of the engineers and suppliers together can benefit the company by reducing the cost of the product and therefore increasing profit. The suppliers can save money by using less expensive materials and manufacturing processes.
Bayesian analysis is a constant conscious and unconscious procedure in our lives, and the interpretation of mixed signals is a challenge. In class we were faced with the problem of how to interpret the moves of a participant whose information we could not see. At a single step this was complex; in aggregate it becomes impossible to accurately assess the probabilities created from multiple mixed messages. A common approach to this challenge is to store only the interpretation of each step. In Updating Beliefs with Ambiguous Evidence: Implications for Polarization (Draft form) Roland G. Fryer, Jr., Philipp Harms and Matthew O. Jackson look at the possible results of Bayes’ analysis with limited storage (such as human memory), and apply them to understanding the polarization of beliefs among agents (people) exposed to the same signals.
According to the model proposed by Fryer et al, an agent with a previously formed inclination as to the state of a situation, when faced with mixed signals, will remember these mixed signals as being true signals for the outcome they were inclined towards. In the provided example an agent, with a prior inclination to state A, sees a series of signals: a; b; ab; ab; a; ab; b; b (3). Because the agent has limited memory, the agent interprets the signals as a; b; a; a; a; a; b; b, seeing more evidence of a then b, when there was actually more evidence of b. The paper follows this model, determining that if the believed probability of a false outcome is high enough, and unclear signals frequent enough in relation to true signals, then it is inevitable that the conclusion reached by the agent will be wrong (10). Furthermore, if beliefs are based on early impressions then early signals alone can create a cascade of evidence (within an agent’s interpretation), similar to what we studied in chapter 16.
The conclusion of this paper discusses the polarization of people with regards to political and social policies. It seeks to answer the question as to why people facing similar evidence (such as the correlation between human activity and global warming) display highly polarized beliefs. The conclusion the paper draws is that, with this model, it is possible for two agents to view identical information and come to different conclusions, while both rationally applying Bayesian analysis. The model is also applied to discrimination, identifying a process whereby discrimination, once formed, can be perpetuated indefinitely (15).
This relates to chapter 16 in that it uses the same type of repetitive Bayesian analysis. The difference is that the subsequent Bayesian steps happen within a single agent, not in a group of agents observing each other’s practices. The limited storage (memory) available to one agent creates a situation whereby the agent only observes her own actions, but does not recall and accurately access the evidence that propelled those reactions; engendering the possibility of a false cascade within a rational agent.
This paper was chilling to read, however in its application to polarization in politics it requires agents to make binary choices when faced with limited storage. Whether or not people do this, even under extreme stress, is an interesting question.
The influence of Apple is undeniable. The popular tech conglomerate recently launched its sixth generation iPhone and, for the first time, split the mobile platform into two models: the flagship iPhone 5S and the reasonably priced, but feature-restricted iPhone 5C. For one company based 6,465 miles from Apple’s cozy headquarters in Cupertino, California, the full influence of Apple and its consumer market is more present than ever.
Only a few weeks after the public release of the two new iPhone models, rumors purporting the early failure of the iPhone 5C began to flood technology sites. By mid-October, these rumors found ground to hold their claims as The Washington Street Journal reported Apple had scaled back iPhone 5C orders from suppliers. While speculation and concern equally arose regarding the demand of this less expensive model, one of the device’s primary suppliers, Pegatron, found themselves in a tough spot after a record-breaking quarter report.
As of early November, Pegatron reports decreased profits for their third-quarter net profit and a dismal outlook for their chance at competing in a marketplace full of successful suppliers including one of Apple’s largest suppliers: Foxconn. The short-term rise and fall of Pegatron’s earnings can be attributed to many factors; chief among which are the notions of information cascades, direct-benefit, and the relationship of markets and beliefs.
When Apple first announced the inclusion of a secondary, less expensive and less robust iPhone model back in September, analysts and journalists speculated about the need for the device with the impressive flagship 5S and the continued sale of the outgoing iPhone 5 models. These commentaries along with reported initial sales figures of the iPhone 5S outselling the iPhone 5C two-to-one despite price differences and availability soon created the common belief that the cheaper, plastic model was overpriced and not worth purchasing. Reviews and comments that questioned the price, features, and purpose of the iPhone 5C further worsened the reputation and direct-benefit value of the model until hitting a tipping point that spurred demand to decrease rapidly – prompting Apple to cut orders for the seemingly unpopular device.
After the initial launch window, the unpopularity and decreasing demand of the iPhone 5C grew alongside positive reviews and praise for the flagship 5S model. This, in turn, greatly impacted the decision-making process for numerous consumers who began to hold the belief that the iPhone 5S or comparable smartphone would be a better choice based on the available information and numerous signals to avoid the iPhone 5C. This information cascade not only further damaged the already dismal reputation of the plastic model but soon directly hurt the principal supplier, Pegatron.
For Pegatron, their quarterly financial report call held in early November after a reported stellar second-quarter net profit must have stung quite a bit due to the very short-lived nature of their success. Shareholders who initially bet on the continued growth and success of Pegatron following Apple’s decision to source them as a primary supplier were quick to “jump ship” as steady share prices dropped drastically following the report call.
With the trend in declining share price and predictions for very little growth in the fourth quarter, it comes as no surprise that investors have been quick to act on the market’s belief that the valuation of Pegatron will continue to decrease for this financial year.
While Pegatron’s fate is far from sealed – especially with the potential increased demand for iPhone 5C models during the upcoming holiday season – it is clear that a combination of information cascades, direct-benefit forces, and market beliefs have greatly prompted a reasonable level of concern internally and among shareholders of the Taiwanese corporation. From the retail stock of a product to the stock prices of a supplier, factors such as information signals, market demand, and common belief of user adaption rate can greatly affect all players in the chain of a single good. This is certainly the case with the rocky recent release of the iPhone 5C and its primary supplier, Pegatron, despite the continued success of Apple.
Don’t count those weak ties out too early- they just may get you a job. LinkedIn is an entire business founded on the idea that weak ties can get you far in the world. Since it launched in 2003, LinkedIn has been helping people create and maintain weak ties for professional networking. It’s become so popular that they often write up tips for new users on how to reach the maximum amount of people, or in other words, how to create the most possible weak ties. This article (and slideshow) offers a few such tidbits. It offers obvious tips, like “put a face to the name,” or have a professionally shot photo as your profile picture. People want to have a good first impression of you, and a good profile photo is a big step in that direction. It also recommends you join and contribute to groups on LinkedIn. Joining a group is a great way to establish a whole bunch of weak ties at once – you automatically have one with all the other people in the group. Not to mention the fact that active contributors to large groups are likely to get noticed by a lot of people in the group, and making yourself stand out above the rest is essential in the highly-competitive job market. They also offer the interesting bit of advice that you should “leverage your colleagues.” Most people focus on only themselves and their own profile, but a colleague’s profile that mentions you or your company can help get your name out there even more than only your own profile. The final bit of advice they give is to constantly refine your profile- to tweak and change it often so that people know exactly what you’re all about. If a business, person, or organization reads your LinkedIn profile and decides you’re worth following, well, there’s another weak tie for you, and maybe just a future career opportunity. Creating a good LinkedIn profile will net you a plethora of weak ties, and as Ch. 3 of the textbook explains, weak ties are the source of most job opportunities.
Even if someone is a weak tie, it doesn’t mean they can’t dramatically affect your life. In fact, I’ve felt the strength of a weak tie more profoundly than most. Several months ago, my father received a message on LinkedIn from an old colleague of his, say his name is Mark, a man he had not worked with since the 90s. Mark said that he would be in New York City for a few days, and invited my father to lunch to catch up. When my father got to the lunch meeting, he was surprised to see not one, but two men waiting for him, one of whom turned out to be Mark’s boss. Introductions were quickly made, and lunch was had. To my father, it seemed like a routine lunch, eating and chatting in the gap between the first and second half of his workday, the conversation not really focused on matters of business at all. However, at the end of lunch, Mark’s boss announced that my father had done a great job at the interview, and promptly offered him a job. My father was floored. He wasn’t expecting anything to come from this lunch – just a reunion with an old friend from work and nothing more. It hadn’t even seemed like an interview. When he said he wasn’t aware that it was an interview, Mark said “I remember how well you did your job when we both worked for [name redacted]. I wanted to catch up with you, and at the same time show my boss how well I thought you’d fit in at our company.” As it turns out, the job offer was far and away better than my dad’s current job, so he accepted within a matter of days. The only catch was, my family had to move from Long Island to Texas. My dad decided it was worth it, and after all was said and done we moved down south. All because a man my dad worked with twenty plus years ago wanted to catch up. If a weak tie can move my family halfway across the country, imagine what it could do for you. Don’t let the name fool you – a weak tie can have a strong pull.
Imagine you really hate the iClicker questions in Networks class. I say imagine, because no one actually hates iClicker questions, right? Turns out, the guy who sits next to you every day also hates iClicker questions. The two of you then turn to a hard life of crime and decide to steal the iClicker receiver from Statler Hall in the middle of the night. Unfortunately, you two aren’t good burglars and the police catch you in the act. They place you in separate interrogation rooms, where you two can’t communicate. Fortunately, the police can’t convict you on the intent of stealing the iClicker and can only charge you with the lesser act of trespassing (robbing students of iClicker questions is a greater crime than trespassing). However, they offer you a deal—if you confess to the crime, you don’t have to go to jail at all, but your partner will be sent to prison for a very long time. You assume your partner in crime has been offered the same deal. If you both confess, you both get sent to prison for a long time. This is called the Prisoner’s dilemma, and in class, we determined that the best thing for you to do is to confess to the crime, even though cooperation would yield better results.
Now imagine that you’re really dumb and you try again with the same person, after you both served your prison sentences and re-enrolled in the class. In fact, you keep trying to steal the iClicker receiver from Statler Hall 185 and you keep getting caught. This situation is now called the Iterated Prisoner’s Dilemma” (1). In a study published in 1980 (http://www.jstor.org/stable/173932), Robert Axelrod showed that in an iterated Prisoner’s dilemma game, there is an effective strategy that can result in both of you getting the lesser trespassing sentence every time you get caught (2).
The strategy is known as Tit-for-Tat, and was “discovered” by Axelrod when he conducted a computer tournament that pitted strategies from different scientists against each other and tallied the total scores. The payoffs for Axelrod’s game are as follows: if both players “cooperate” (refuse to confess), they both receive 3 points. If both players “defect” (confess), they both receive 1 point. If one player cooperates, but the other defects, the player that cooperates gets nothing and the player that defects get 3 points. Tit-for-tat, which embodies the idea of an “eye-for-an-eye,” came out the winner against strategies ranging from always cooperate to always defect.
In Tit-for-Tat, you always start out cooperative. So, in your iClicker situation, you would not confess to the police. If the other player does the same, you both win. However, if the other player defects (your accomplice confesses), you get screwed. The next time you play the game (when you get caught again), you defect because the other player betrayed you in the previous game. If the other player continues to defect, you continue to defect However, if the other player cooperates, you choose to cooperate in the next round, which in essence, means that you forgive him for backstabbing you in the previous game.
The results for Axelrod’s study is very interesting, because it shows that in Prisoner’s Dilemma games, the people who are “nice” (they don’t defect) will almost always come out on top, despite the saying “nice guys finish last.” Tit-for-tat is a “nice” strategy because it assumes goodness in everyone, and fosters cooperation and clemency. Axelrod’s research is also very relevant to our discussion of Nash Equilibria in the Prisoner’s Dilemma game (Chapter 6) because it shows that the outcome of the Prisoner’s Dilemma can be different if the game is repeated.
Of course, the situation I described with the iClickers is very silly and unrealistic. However, the tit-for-tat strategy had been in practice far before Axelrod confirmed its efficacy. In World War I, soldiers in trenches would not fire on each other unless the other side shot first (3). This strategy led to lower casualties for both sides. During the cold war, the U.S. and Russia followed the doctrine of Mutually Assured Destruction, which was essentially a tit-for-tat strategy (You bomb me, I bomb you). Iterated Prisoner’s dilemma strategies can be applied to many situations ranging from business deals to international relations to friendships.
Thus, the next time you get into a Prisoner’s dilemma, remember that cooperation is a very good strategy if you know you’ll repeatedly find yourself in the same situation. Or, you can just get out of bed at 10:00am and click a few buttons 3 times a week.
(2) http://www.jstor.org/stable/173932 (Effective Choice in Prisoner’s Dilemma, Robert Axelrod)
(3) https://en.wikipedia.org/wiki/Live_and_let_live_(World_War_I)keep looking »