@MichMae99 9 October 2020 more from that month

Information through internet When sociologist ask people if they waste food, people give the only correct answer. It's wrong to waste food. When sociologist survey the contents of the same people's garbage, they get a more accurate answer.

Photo source: https://www.google.com/search?q=internet&client=ms-android-huawei-rev1&tbm=isch&prmd=vimn&sxsrf=ALeKk01R5r1g5SrTBCYxEAi1BwLTWtivvA:1602248993750&source=lnms&sa=X&ved=0ahUKEwikp_TQyqfsAhVSyYsBHWkZDBMQ_AUIFigC#imgrc=IPT4SILXw2qYAM Just imagine how much more information is available trolling through internet searches. This also show that internet can be used to improve our understanding of human behavior, thinking, emotions, and preference. The basic idea is that if you ask people about their behavior or their preferences in surveys, even anonymous surveys, they will often lie. People do not like to admit to low-brow preferences; racists do not want to admit to their prejudices, most people who watch pornography do not want to admit to it, and even voting is often misrepresented; some people who voted for Trump would not admit to it. But, by analyzing immense datasets from Google, public archives, social media, and the like, Seth Stephens-Davidowitz has been able to unearth a lot of fascinating answers to puzzling questions. For example, he is able to predict, through Google searches for various symptoms, who is likely to have early stages of pancreatic cancer. He can predict epidemic breakouts of some contagious diseases well before they are announced by the CDC (Center for Disease Control). He shows that the single factor that correlates with voting for Trump is that of racism. Then there are the fun factoids, about the sorts of things that people search for most often on Google. Most commonly, the search "Is my son ..." is followed by "gifted", while the search "Is my daughter ..." is followed by "overweight". That tells us something about stereotypes for the way people think about their children. Interestingly, the release of a new violent movie in a city is correlated with a *decrease* in violent crime in that city. Perhaps the reason is that violent people who are watching the movie are not out on the streets, committing crimes. And here we get to the main problem with this sort of analysis. Undoubtedly, the research and analysis of big datasets is done correctly. However, once a surprising result is found, understanding the motivations behind the online activity are often subjective and open to interpretation. While this book is very careful about its underlying assumptions, it is a slippery road to getting the correct interpretations and explanations.