Bayes’ Rule in determining Oscar Awards
For all the movie lovers out there, the Oscars is one of the events we look forward to every year. We cross our fingers, say our prayers, anxiously sit and wait for our beloved stars to (hopefully) win an award. Thanks to Bayes’ Rule, we no longer have to do that. We can predict who […]
Information Cascades within Cancel Culture
Being in a highly connected society comes with the rapid spread of information, for better and for worse. As the power of social media establishes countless avenues of communication, it also creates the possibility of scrutinizing and identifying any public figure’s words, actions, and personal background. Consequently, cancel culture has become a prominent force driving […]
Tech Giveaways on campus and Diffusion of Innovation
When walking on campus, we sometimes see giveaway campaigns or free trial events from various tech companies. Does this actually work? How can we use networks to explain the benefits of a giveaway? We can take a look at the reason behind giveaway campaigns with cascading behavior in networks we learned in class. In […]
Stock Market Bubbles
https://seekingalpha.com/article/4522405-tesla-stock-the-last-bubble-standing https://www.investopedia.com/articles/investing/052715/guide-understanding-information-cascades.asp A fundamental illustration of herd behavior or information cascading is the presence of stock market values, ranging from the relation of general stock valuation to a stock market bubble. To summarize, a stock market bubble is driven by a common consensus of investors (most consisting of private, independent investors) that have an incorrect […]
Ads and Big Tech
https://medium.com/@profgalloway/elephants-in-the-room-31e072ea75ae In class, we learned about how companies like Google make money through Ads. We discussed the market based around the information seeking behavior of millions of people making their way through the Web, and the system of clicks that generates profit. Digital ads made Big Tech companies like Meta and Google into what they […]
Topic-Specific Information Cascade on Twitter
The study above examines the patterns of how information and behavior spread among Twitter users by investigating characteristics of hashtag cascade in various topics. The paper analyzes hashtags related to four categories on Twitter: Earthquake, Politics, Media, and Entertainment. For each topic, they computed cascade ratio, tweet ratio, and time interval to gauge user influence […]
Information Cascades and the Salem Witch Trials
Mass hysteria about the supernatural and misdirected religious fervor launched a series of prosecutions for witchcraft in 1692, Salem Massachusetts. For those that don’t know, this event was infamously named “The Salem Witch Trials”. It began with two girls, Abigail and Betty, who had appeared to be possessed by the devil. Although a physician had […]
Limits of Network Effects and the Impact on Tech
The growth of companies like Facebook, Twitter, Snapchat, and TikTok has always been reliant on the size of the user base. Social media companies are the best examples of business models that rely on network effects for their success. When these companies started, they relied on their networks being big enough to attract more people […]
Bayes Theorem and Predictive Policing
Source : Why SA should embrace artificial intelligence for predictive policing – Moneyweb The source essentially introduces what predictive policing is: predicting crimes and preventing crimes before it happens. The source explains how the foundation of predictive policing is built on Bayes’ theorem. Bayes’ theorem tells us the probability of an event based on prior […]
Making more accurate medical diagnoses using Bayes’ Theorem
Bayes’ Theorem is often applied in economic contexts, but it can also be applied to inform decisions in the healthcare industry. This study, conducted by Dujin et al., looks at how diagnostic-informed diagnosis of malaria in Kenya can improve accuracy in medical decision-making and ultimately reduce the probability of overdiagnosis and over-prescription. Dujin et al. […]
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