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The anatomy of information cascades in the classroom

This observational study analyzes how information cascades appear and evolve and what factors are relevant for the formation of cascades within a classroom through online learning platforms. This study found that students don’t prefer to share the content given to them by professors, rather they prefer to share the content they find themselves. It was also found that high-performing students shared documents with more information, or high information. The study defined an interaction as a communication between two students sharing some documents or messages. They recorded interactions such as conversations in the course Facebook Chat Canvas, documents shared on online platforms, and files shared as URLs by students in their course specific Facebook accounts. There were informal resources, such as blogs, Q&A sites, or online tutorials, as well as formal resources, which were manuals, peer-reviewed papers, and presentation slides. Results found that only a fraction of the documents from the educational portals, user accounts and social platforms were propagated to the students and then never accessed again. Although student content was re-shared more frequently than professor content, students did reference the professor content. Overall, longer information cascades contained content suggested by students, while shorter cascades contained content shared by professors. Some factors that led to a cease in the information cascade were information density, length of the content, and whether the student was high-performing or low-performing.

This relates to the concept of information cascades in lecture, in which the spread of technology, products, social movements, or opinions can be analyzed. This study revealed a few factors behind information cascade within the classroom. Content suggested by students tended to be shared more, with longer information cascades. It was also found that high-performing students shared content faster, in more complex cascades, and more regularly than mid- and low- performing students. More content shared led to longer cascades. We can also look into the idea of low threshold compared to high threshold. As learned in lecture with thresholds and what may lead to a cease in the cascade, this study touches upon characteristics of the content that may lead to a cease in the cascade. Such factors include information density or information of documents. So, this information cascade is a bit different from lecture in that it is not that a cascades stops because there needs to be a certain number of your neighbors using the new technology for you to switch, but rather if the content that is being shared would be beneficial or valuable to a student based on the length, or content. A student may stop the information cascade if they don’t find that the content is valuable enough to pass on. Overall, this study emphasizes that information cascades exist within classrooms and online platforms, as students are able to pass along information and content they find helpful to other students, and then the other students will continue to pass along the information if they find it helpful.

 

Link: http://onlinelibrary.wiley.com/doi/10.1111/bjet.12567/full

The rise of sexual harassment cases and information cascades

Article: https://www.ft.com/content/6973e6d6-d047-11e7-9dbb-291a884dd8c6

 

The article linked above, written by Gillian Tett, discusses the election of Donald Trump and the recent wave of sexual harassment cases. In this article, Tett, explores two factors that she believes contributed to the new surge of sexual harassment cases. These two factors, she states, are Donald Trump and information cascades facilitated by the prevalence of social media. According to Tett, Donald Trump and his election to the Presidency contributed to the rise of sexual harassment cases by empowering feminist. She states that, “When [Donald Trump] was elected, shattering hopes that Hillary Clinton might be America’s first female president, most observers presumed that his victory was bad for women. However, a year later, it has become clear that Mr. Trump has unexpectedly empowered feminists. One early sign of this was the women’s’ marches.” Tett’s claim is that Donald Trump’s election, empowered women giving them a figure to stand against. Someone who actively strives to damage any social progress made in this country.

The second key factor that Tett touches on is that of information cascades contribution to increase in sexual harassment cases. According to Tett, information cascades contributed to the upsurge of the sexual harassment cases and experiences being revealed because with the commonness of social media in our lives, information about these cases can be spread easily and accessed by large amounts of people effortlessly. This information can then be broadcasted by one victim and spread to another, who, might be inspired to share their story and thus continue the cascade. Tett states that:

If a woman wanted to complain about sexual harassment allegations two decades ago, there was a slow-moving bureaucratic and legal process. And if a reporter wanted to corroborate a story, this entailed months of painstaking research. But in cyber networks, information can spread at lightning speed, beyond the control of lawyers or traditional authority figures. Journalists can appeal for tips and be inundated within minutes. Once-powerless victims have a megaphone. Isolated victims can suddenly congregate into a crowd. Informational cascades, in other words, overturn power structures.

Information cascades in conjunction with the catalyst Donald Trump is, provided the optimal conditions for sexual harassment occurrences to finally be brought into the light.

The Weinstein Effect as a Tipping Point

The article linked below is a conversation between NPR host Noel King and NPR writers Mary Schmich, Elizabeth Blair and Alexandra Schwartz about the recent revelations surrounding sexual assault by powerful men not necessarily in Hollywood, but across industries. “The Weinstein Effect”, as the writers have dubbed the phenomenon, refers to the growing list of women coming forth with their stories of sexual harassment and assault by powerful men after Harvey Weinstein was exposed earlier this year. Allegations against Weinstein, an American film producer and former top film executive, were brought to light through an expose done by the New York Times detailing decades of allegations of sexual misconduct by several women. Since The Times’s expose, however, several women have come forth with allegations surrounding other men as well.

 

Similar to the tipping point in cascade models we discussed in class, the NPR writers engaging in this conversation argue that the Weinstein scandal was a tipping point in the cascade that occurred after. Although there were several factors that contributed to the increase in women coming forth with their stories of sexual harassment/assault – President Trump and the Access Hollywood tape is one of the factors mentioned – the Weinstein scandal was the tipping point for the trend that occurred after. As we covered in class, a tipping point refers to the point in a situation at which a seemingly minor development instigates a cascade of behavior. In this case, the Weinstein scandal was the tipping point for many of the movements that followed – the Me Too Movement, the spike in reports of harassments and assaults by women in Hollywood, the accusations against Kevin Spacey, Matt Lauer, Roy Price, Charlie Rose. An interesting and relevant application of tipping points, the Weinstein Effect refers to the cascade of women coming forth with their stories of powerful men engaging in sexual assault and/or harassment with the Weinstein scandal being the tipping point for the cascade itself.

 

Article: http://www.bbc.com/news/entertainment-arts-41594672

How social media affects tipping point

We have learned the definition of the tipping point and how marketers use that to build their strategies for success marketing. Tipping point is an important information that marketers need to see what is wrong with the current strategy and guides them to look for solutions. Any points right below tipping point will lead the business to failure and any points above tipping point can attract many more customers. In the past, advertisement methods were the only solutions to improve business situations and attract more customers, so marketers used advertisements to raise the point to be above the tipping point.

With the rise of social media, it has become much easier for both individuals and organizations to reach their possible audience. This article examines how social media have viral superpower and compares old period where traditional advertisement methods were used and current period where social media controls who sees what. According to the article, Lady Gaga sold 305,000 copies in 2 weeks by spending millions on bus advertising, billboards, 2 pop up stores and performing countless interviews. On the other hand, Beyonce posted her new post about her album on her social media and was able to sell 828,733 copies in three days.

Both results prove how powerful social media is and spending on traditional advertisement methods may be a waste. It is so much easier to raise the point above the tipping point and more people will be convinced to follow the herd. Although social media sounds like an answer in marketing but businesses can lose customers as easy as it convinced them. If any person or organization loses reputation and lose many customers, just posting something on social media will not bring the point to tipping point.

Is this the Social Media Marketing Tipping Point?

North Korea and Evolutionary Game Theory

https://www.ft.com/content/27a20c72-d472-11e7-8c9a-d9c0a5c8d5c9

North Korea claims missile puts all of US in range, Financial Times

Despite the fact that the United States and several neighbour countries kept making strong oppositions and warning North Korea of its possible aftermath if it continued its missile test, North Korea didn’t stop its nuclear development plan. According to the recent missile test of North Korea, North Korea has already gained the capability to put all of the United States territory inside of its missile range. Based on traditional international politics logic, strong opposition signal and possible harsh punishment can help deter countries from taking certain actions. However, such logic seems to be not applicable in the North Korean nuclear crisis case.

Thinking from an Evolutionary Game Theory angle might help explain why nuclear weapons are so attractive for North Korea. Although a shared agreement on nuclear nonproliferation was formed in the past one or two decades, most of the major players in the current world have nuclear capacity. Consider the situation that most of the players have nuclear weapons and only a small factions of players don’t, in which it is possible that the payoff of countries that have nuclear weapons is at least equal to if not larger than the payoff of countries that do not have nuclear weapons. Moreover, because of the lack of mutual understanding, countries don’t have an actual table of payoff as the one we get in problem sets. Then, North Korea’s anticipation of payoff may be generalized from previous history cases. The fact that most of the countries that tried to acquire nuclear weapons didn’t suffer from harsh punishment and that some of them even gained a stronger leverage and higher international status also give North Korea the strong incentive of acquiring nuclear weapons, despite the possible punishment of the United States.

Artificial Intelligence and The Kentucky Derby

 

Artificial intelligence has come to the Kentucky Derby.   According to a recent article in Forbes, the Kentucky Derby is partnering with an AI company to apply the science behind artificial intelligence to “handicap the race.” According the Forbes, the AI company correctly predicted the Superfecta outcome of last year’s Kentucky Derby, which means that the technology could predict the first, second, third and fourth horse correctly in the correct finishing order.  “To put it all in perspective, getting the first four horses correct is such a tough task that a $20 Superfecta bet on last year’s race would have returned $11,000.” For this year’s Kentucky Derby, the same AI will attempt to predict the results and then release the predictions so that the bettors will be more informed.  In theory, this informed universe of bettors will result in odds that more accurately reflect the risk adjusted potential outcomes of the race.   The AI company, Unanimous A.I utilized technology it created called Artificial Swarm Intelligence. Dr. Louis Rosenberg, founder of Unanimous AI, emphasized that “[W]hile predicting sports always involve a large element of chance, Unanimous A.I. taps the intelligence of groups and evokes the best possible prediction based on the available information.”  I was curious so I did some additional research on Swarm A.I and learned that this technology attempts to combine the ideas of many participants to create the outcome of one brain, which is similar to how flock of birds use their combined intelligence to for navigation. The Swarm AI uses the human input of many to create datasets that can be used to create predictions of future events or conditions. The article explains that the predictions being made concerning the Kentucky Derby will be made with the help of Swarm AI in combination with data from top handicappers and other horseracing experts.

 

As discussed in class, handicapping horse racing involves betters distributing their wealth across a wide range of races. Our conclusion was that the bettor always bets his belief about the potential outcomes. In effect, the proportion of wealth that one puts on a horse should be based on the probability the bettor places on his belief that any one horse will win the race. This fact, combined with the new variable created by the use of Swarm AI in this year’s Kentucky Derby  raises new questions for the bettors at the race. Most likely, the odds this year will most likely be more spread out because of the input from Swarm AI, which will create more viable choices.  This may create more incentives to bet on the underdog. In my mind, even though this may appear like an appealing strategy based on AI, the science is untested and a bettor may still do better by just betting his beliefs.

https://www.forbes.com/sites/alexkay/2017/05/03/kentucky-derby-partnering-with-a-i-company-that-correctly-predicted-last-years-superfecta/#10f231552aba

Artificial “Swarm Intelligence” Says Vladimir Putin Will be TIME’s Person of the Year

 

 

Preparedness for a Diseasae Outbreak

How Ready Are We for a Pandemic? We Asked an Infectious Disease Expert

 

This article discussed the probability of an upcoming disease outbreak. Despite countless advances in technology, we are still incredibly susceptible to diseases. Furthermore,  some technology, such as antibiotics actutally increases the probability of a disease outbreak when it is used incorrectly. Currently, antibiotic resistance is at a crisis level, meaning there is a high risk of a disease outbreak. As it stands, the current administration is not adequately prepared for a disease outbreak. This is particularly troublesome because the world is long overdue for a major disease outbreak. It is estimated that the next viral disease outbreak will happen by 2070. With this approaching probability, it is important that policies are in place that is able to rapidly reduce the spread of a disease, each by decreasing the contact that sick individuals have with the healthy population, such as with quarantine, or by reducing the probability that an individual contacts a disease, such as vaccination.

Global Risk of Madagascar’s Pneumonic Plague Epidemic is Limited

https://www.sciencedaily.com/releases/2017/11/171130093814.htm

This article is about the recent uprising in pneumonic plague in Madagascar. Currently, mathematical models project the diseases reproductive number to be around 1.73. The study says that the probability of worldwide spread is very low, around 0.1 person per the 78 day period they evaluated. This disease is dangerous, however, because of its high fatality rate and the time offset between onset and reporting of cases. The only way someone can be infected is through airborne droplets or direct contact with a diseased one’s blood.

This study relates well to our study on epidemics. Firstly, they report a reproductive number of 1.73, and though this is small, it is still above 1 which means that the disease will persist unless additional measures are taken. Given the fact that the disease has broken out in Madagascar and that is has a low probability of spreading outside of Madagascar right now, a positive suggestion would be to increase sanitary measures, decreasing airborne particulates and contact with diseased fluids. Also, by recognizing and treating the disease early on with antibiotics the effects and spread of the disease can be lessened.

 

HIV Epidemic in Europe

This article, posted by Sputnik International touches on a study completed by the World Health Organization (WHO) and the European Center for Disease Prevention and Control (ECDC) that found surprising results in terms of the number of new cases of HIV. One of the more surprising statistics was that just between 2007 and 2015 there was a 50% increase in the number of new cases per year. Only 18.2 new cases were identified per 100,000 people, which is a relatively low percentage of the total population, but there also may be a lot more unaccounted for cases that are not included in that data. In 2016 alone, over 160,000 people throughout Europe contracted HIV, which leads towards AIDS that has no definitive cure and can be deadly. It takes about three years to get AIDS after HIV, which is likely long enough to prevent or stop if treated early, but if one does not know or care that he or she has HIV, then getting AIDS eventually is almost certain.

When we relate the topic of this article to what we learned in class about epidemics we see a close relation and can understand at a deeper level why more people are contracting HIV. From the formulae we learned in class we know that the number of people one affects is R=pk where R is the average number of people one will affect with HIV, p is the probability of contagion which in this case is the probability that in an encounter one transfers HIV and k is the number of people that one affects on average. With HIV, the p value is quite high and is relatively constant, but the k value changes. Thus we can conclude that either infected people are infecting more people and do not realize they have it or more interactions are happening in general. We know that if R is greater than 1 than the epidemic will spread so if the number of people is increasing at a high rate like the study found, R must be greater than 1 for Europe and HIV is spreading as opposed to if R were less than 1 it would be decreasing faster than it was growing.

https://sputniknews.com/society/201711291059520080-HIV-epidemic-europe-growing-alarming-pace-who/

Game Theory of OPEC Production Cuts

https://seekingalpha.com/article/4055294-opec-production-cut-failure-next-oil?page=1

Earlier this year OPEC (Organization of Petroleum Exporting Countries) agreed to cut oil production in hopes that cutting supply would raise prices favorably for the supplier. The countries that OPEC is comprised of control a large enough amount of global petroleum production that there is merit to their effort, and they have succeeded with a similar strategy in the past. The projected yield on the strategy has not met fruition however, and halfway through the deal we are instead seeing oil prices dropping. This is a product of a changing oil market, with new production occurring in Alaska, Canada, and Brazil that was largely underestimated by OPEC. With new players in the market dropping pushing prices down, individual countries within OPEC are ramping production back up in hopes to get there slice of an increasingly competitive market.

Applying a lens of game theory to OPEC’s struggle to control the market sheds light on the situation at hand. Initially, the game is defined by the 12 oil producing nations that comprise OPEC, and the decision of each individual country on how much oil to produce. In an unrestricted market, each of the 12 countries produces at maximum volume and compete against one another to sell petroleum which creates downward pressure on oil prices and cuts into the producer’s margins. This issue can be amended, however, if the countries agree to cut production volume collectively and benefit from the rise in prices that follows supply shortage. The game theory issue lies here in that if production gets cut and prices rise, it is in every individual countries best interest to undermine the rest of the group and produce at maximum volume, resulting in full production at increased sales prices. When every country takes advantage of this opportunity, supply returns to the previous volume and prices lower back to equilibrium.

While this issue of incentive is sometimes addressed by having a stronger centralized OPEC, the members of OPEC need to understand that the rules of the game they are playing in are changing. With massive shale production from Alaska and Canada feeding North American fuel needs and Brazilian oil help South America, in conjunction with oil flows from Russia, we are seeing OPEC’s share in the market place and overall purchasing power weaken severely. When they are no longer able to control prices in the market, there unity and strategic production stops are going to have little impact on the market and instead only put downward pressure on their own profit, as exemplified by this year’s round of production cuts. The only way to adapt and maintain their strategy would be to increase the number of players in their organization so that they can control enough of the petroleum market to once again drive the supply.

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