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wharton case studiesWharton case studies -For every data source, you have to think: What is this data source?That’s a really, really subtle pattern that is hard to pick up without massive data sets, and it almost suggests a new kind of medicine.I’ve already talked about some of the clues I already had right before the election that suggested to me Trump was going to win. One, you can see based on whether people search for “how to vote” or “where to vote” before an election whether they’ll actually turn out to vote.We tend to make horrible predictions about what we’re going to do in the future. That has an impact when you’re thinking from a global perspective, whether it’s in business, politics, or on a variety of different fronts. It’s just really interesting to compare the differences between countries that can be revealed in this data.The optimistic scenario is that we would have insights into really, really important areas — health, racism, sexuality — and really learn how to improve society.Knowledge@Wharton: One of the areas you look at is sex.“[If you] go by conventional wisdom, racism is considered a Southern issue….But I think with big data, it’s really surprisingly easy to come up with a new, important idea in a really big area.Knowledge@Wharton: One of the things that may have helped revolutionize big data and our understanding of this, which you write about, is Google Trends. Google Trends can show you where different terms are searched, what place they’re searched more frequently, and then you can also see how things are searched over time.Stephens-Davidowitz: Yes, I think surveys have big holes in them.I think a lot of people, any time they see numbers or data, they say, “Oh, that’s reliable.” But a lot of data sources are crap — pardon my language.Knowledge@Wharton: One of the long-held beliefs about this was that racism is more of a Southern phenomenon, but your data showed that is not necessarily the case. If you ask in surveys or go by conventional wisdom, racism is considered a Southern issue.Everyone says they’re going to vote, and then many of them don’t.” When you ask them, people say “I’m going to watch a documentary,” or “I’m going to watch avant-garde French films.” Then Friday comes around, and you have that in the queue, and they ignore it and watch the same lowbrow comedies or romance flicks that they’ve always watched.Knowledge@Wharton: You are a self-professed cynical person, yet your life is in data. With a lot of the traditional data sources, there are incentives for people giving you that data.Knowledge@Wharton: That’s part of the reason why a lot more companies are really looking at analytics, and looking at data to get a truer understanding of what consumers are thinking, correct? I think it’s also just that you have to be careful.Knowledge@Wharton: So is this going to be a growth area for the U. economy: People who can do the analytics, who can understand how to use this data to really make the impact on companies and people alike? But it’s surprising how much it is a creative process.Some of these new data sources that are coming can dramatically improve our understanding of these countries.And they found really, really subtle patterns that are predictors of eventually getting a pancreatic cancer diagnosis.But I think that may be because in the South, there’s just less need to hide that racism.wharton case studiesThere’s obviously a lot of lying around sex because it’s an uncomfortable, taboo area.And they would seemingly give you much better predictive tools to use in fostering growth or avoiding pitfalls in various economies around the world. I think I tend to be a very cynical, skeptical person, so when I hear a term like “big data,” or when I hear a buzzword, I’m just kind of like, “Ugh, these things are so silly.Then you compare those people to similar people who never were diagnosed with pancreatic cancer, and you look in the prior months what symptoms were they searching for.I talk about Premise, which is a company that basically just goes around taking pictures of economic activity in developing countries, and from those pictures is able to give estimates of inflation rates, interest rates and lots of other things.Knowledge@Wharton: Do you believe, though, that we are getting to a point where people have a better understanding in general about all the data that is out there?Knowledge@Wharton: You immerse yourself in this data on a daily basis at this point.If, in general, people lie to make themselves look good, then we’re going to have an overly optimistic perception of who people are.You can’t really trust when people tell you in surveys that they’re going to vote.Knowledge@Wharton: If people or companies were able to use this data in a more coherent, more effective manner, what do you think the impact in general would be for the country, or for society?Stephens-Davidowitz: Well, there’s an optimistic scenario and a pessimistic scenario. The pessimistic scenario is that companies would use this to take advantage of people, to get them to spend more money that they don’t have, or spend more time on their websites even though they don’t need to be on those websites.Stephens-Davidowitz: No, I think that search by itself is not revealing, because you may search Clinton because you love her, or you may search Clinton because you hate her. But the order in which candidates are searched does have predictive power.Knowledge@Wharton: Going back to the political realm, you discuss in the book that the data and what was out there on the internet did suggest that President Trump was going to be the person to win, not only the Republican primary, but also the general election, correct?I just said, “Think of a new business in education or think about a new business in health, think about a new business in politics, and how using the tools of new data and big data would help you with that business.” And by the end of every single presentation, all of the students said, “Why doesn’t this exist? This should exist.” It’s usually hard to come up with something new, because smart people have been spending their whole lives trying to find things that should exist, things that people want.And if people go “Clinton/Trump poll,” they’re much more likely to go Clinton’s way.The idea that we would be able to glean information that might lead to cures for diseases, or be able to take a more effective preventive approach, being able to catch diseases before they become worse — those things would have an incredible impact both on the people in this country, and also the economics surrounding health care. In one of my favorite studies, they used search data and found people who made searches such as “just diagnosed with pancreatic cancer.” And you know when someone makes a search like that, they probably just got diagnosed with pancreatic cancer.The real divide in racism these days is not South versus North, it’s East versus West.I talk about night lights data, which can measure the economy just based on how much light is being produced.But what this revealed is that African-American turnout was going to be much lower than in previous elections. Then there is a really subtle clue that I think is fascinating: The order in which people search for candidates can give a tip off of which way they’re going to vote.If you look at the Google search data, which is more honest, you see many of the areas with the highest racism are Northern places: western Pennsylvania, eastern Ohio, upstate New York, industrial Michigan.And Netflix just realized they should ignore what people tell them, and instead focus on what they actually do, and let the algorithm tell the story. Knowledge@Wharton: This also could help us understand more clearly how this country may be different compared to, say, China or France or Germany. wharton case studies But what people click on, what people purchase, what people search — that’s more valuable than many of the other sources that you might consider.Stephens-Davidowitz: I like to say that big data is so powerful that it turned me into a sex expert, because it wasn’t a natural area of expertise for me.It was not considered a scholarly source; it was just more a fun kind of PR source for Google, potentially. What we like and dislike, whom we chose to associate with, and so much more — a steady stream of data that can be quantified, sifted and analyzed en masse with the data from everyone else to reveal patterns previously hidden, sometimes things we’re not even aware of about a visiting lecturer at Wharton, Stephens-Davidowitz joined the Knowledge@Wharton Show on Sirius XM channel 111 to talk about what properly analyzed big data can reveal about our political views, our health, our biases and more.Stephens-Davidowitz: It’s thrilling — the possibilities are really mind-blowing, and in big areas.This is, as I say, probably the most important data set ever collected on the human psyche, and definitely a really important tool for researchers to focus on.When it first came out, it was considered a little bit of a joke.Whereas searching “indigestion” by itself is not a risk factor.Because it’s seemingly a fairly common story about how we really, truly don’t understand all of this data.I mean, this is an open-ended sector right now, in that there is data on everything and anything you could potentially want to have an effect on.I think they get a little uncomfortable with the wild world of the internet, where data tends to be more unstructured and a little bit different than they’re used to. Knowledge@Wharton: There’s not much doubt that our digital footprints say a lot about who we are, but I get the sense that people, to a degree, still scoff at the idea that so much can be gleaned from all of this information. Some people have this traditional notion of what data is.This could be something where you could literally go from business to business and be able to collect data on a daily basis, correct? For the end of my Wharton class, we had a group presentation and I gave them very, very broad topics.You could play around, learn what fashions were popular, what celebrities were popular.Stephens-Davidowitz: I think there were definitely clues. It’s one of the most common questions I get: “Can you use Google searches to predict elections?Knowledge@Wharton: Throughout the book, you tackle some of the bigger issues that we have in society, like racism and child abuse. And there are certain sources, such as Google, which I focus a lot on.Nigeria, I think the biggest economy in Africa — one time, they realized there was a flaw in their GDP estimate and overnight, they changed the estimate by 90%.So I think surveys have been dramatically overvalued, and really are going to play a much smaller role in the future as some of these new internet data sources become more accessible.But I’m not cynical at all about what you can learn if you know the right data to look at.Knowledge@Wharton: And in contrast to that, a lot of these surveys that come out proclaiming data may not necessarily be as accurate as they would lead people to believe. wharton case studies And there were many more searches for Trump/Clinton polls in certain key states in the Midwest.So a company could save money by not giving loans to people who end their requests with “God bless you,” which is pretty scary.Maybe it’s a bit of a gradual process to really get a handle on a lot of this.” And it’s a little difficult, because we’ve only had four elections in which Google search data has been around, so it’s a little challenging to predict their models.So when it comes to really important areas like the ones you mentioned, we can get really new insights into who we are.It’s just the latest, hottest fad.” But I’ve been studying this for five years. And I’m constantly blown away by what you can find. It’s really a revolution in our understanding of people and the world. I think in some sense, it confirms my skepticism, my cynicism in that you can’t trust what people tell you.Stephens-Davidowitz: I think there are definitely concerns about the power of big data.For example, if you use the word “God” in a loan request, you’re 2.2 times more likely to default, 2.2 times more likely not to pay it back.Stephens-Davidowitz: I think we’re getting there pretty fast. I think because it initially was considered so strange that you could just understand people from their internet behavior, it hasn’t really been the subject of as much academic research as it should have been. When you think “big data,” you think it’s this very technical thing, and it’s all about statistics and a left-brain, nerdy pursuit.And yes, this was a big theme — really nasty searches about Obama as soon as he was elected.Then also, from a business perspective, of course, the data is just horrible from some of these countries.So traditional data in some of these countries is really, really bad.Knowledge@Wharton: So was there an implication that could be gleaned from just having Clinton in a search, whether that included Trump with it or whether it did not?ly connected era, all of us produce enormous numbers of data points every day. They think of it like a representative survey: You have clear questions with check boxes that people can answer very clearly.But if we know the truth, in many areas, unfortunately, we’re going to learn darker things about people, and racism is one of the areas. One of the most surprising things I found right away in this data was the shocking number of racist searches people make, basically looking for jokes mocking African-Americans.Going after little questions doesn’t make sense with big data.But I think within four to eight years, we’re going to be able to use this data to predict elections very, very well.If people searched “Trump/Clinton poll,” they’re much more likely to go Trump’s way.A lot of data is really unreliable, and a lot of data is reliable.And there are all kinds of data points which will lean one way or another in these areas. People are just really honest and tell Google things they may not tell anyone else. wharton case studies I’ve already talked about some of the clues I already had right before the election that suggested to me Trump was going to win. One, you can see based on whether people search for “how to vote” or “where to vote” before an election whether they’ll actually turn out to vote. wharton case studies

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