{"id":73009,"date":"2022-07-28T09:20:00","date_gmt":"2022-07-28T13:20:00","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=73009"},"modified":"2022-07-28T11:14:16","modified_gmt":"2022-07-28T15:14:16","slug":"big-data-information","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/big-data-information\/","title":{"rendered":"How Big Data Provides New Information"},"content":{"rendered":"\n

What types of information does big data provide? How does it get this information?<\/p>\n\n\n\n

In Everybody Lies<\/em>, Seth Stephens-Davidowitz says big data opens our eyes to new types of information that weren\u2019t previously available. We can find this new information from search engines and unconventional data sources.<\/p>\n\n\n\n

Keep reading to learn where this big data information comes from.<\/p>\n\n\n\n\n\n\n\n

Words, Words, Words<\/h2>\n\n\n\n

There\u2019s nothing new about using words as data. As Stephens-Davidowitz points out, linguists, social scientists, historians, and others have studied words and word usage for a long time. But big data<\/strong> information dramatically enhances the type and volume of words researchers can study<\/strong>. (Shortform note: It\u2019s this enhanced volume<\/em>\u2014another of the three Vs\u2014that makes familiar data like text into big data. Thanks to the sheer volume of text databases and the ease of searching and comparing texts, it\u2019s easier than ever before to study how words are used and combined across many different contexts.)<\/p>\n\n\n\n

Stephens-Davidowitz himself bases most of his insights and arguments on search terms used in Google and other search engines. Search engines\u2014and the databases of information they compile as users use them\u2014are a relatively recent invention and represent a new source (or variety<\/em>) of data for researchers and analysts.<\/p>\n\n\n\n

Stephens-Davidowitz points out that computers also make it easy to analyze large volumes of text and\/or speech that would be difficult or impossible to deal with manually. For example, he cites a study of word frequency in Facebook status updates and shows how word usage breaks down among gender and age lines\u2014for example, perhaps unsurprisingly, he demonstrates that college-age people post about \u201cstudying\u201d during the \u201csemester\u201d whereas 20-somethings drink \u201cbeer\u201d when they aren\u2019t \u201cat_work.\u201d Similarly, he explains that researchers can use sentiment analysis to determine the overall emotional tone of a body of text. <\/p>\n\n\n\n

(Shortform note: While Stephens-Davidowitz is excited about how academic researchers can use text analysis\u2014for example, he cites studies that use sentiment analysis to map narrative trajectories in works of fiction\u2014most of the practical application of these techniques seems to take place in the business world. For example, businesses use text analysis<\/a>  and sentiment analysis<\/a> to gauge customer interest and reactions, detect problems early, and improve customer service.) <\/p>\n\n\n\n

Unconventional Data Sources<\/h2>\n\n\n\n

Though Stephens-Davidowitz specializes in using search records, text databases, and other similar types of data, he points out that there are new data sources that researchers have only recently started to tap. These data sources show that big data isn\u2019t just about bigger databases of traditional information\u2014it\u2019s also about how new technologies let us turn more things into data<\/strong> by making them easy to measure, collect, compile, and analyze.<\/p>\n\n\n\n

For example, Stephens-Davidowitz suggests that bodies can be data<\/strong>. He describes how consultant Jeff Seder helps buyers choose winning racehorses (Seder and his colleagues once advised a client to re-buy the horse he had just put up for auction\u2014that horse was American Pharaoh, who went on to win the Triple Crown). Seder\u2019s secret is that instead of looking at traditional horse judging factors like pedigree, he found anatomical factors (like left ventricle size) that correlate to race success. <\/p>\n\n\n\n

(Shortform note: Body-based data is now far more prevalent than in Stephens-Davidowitz\u2019s 2017 account. Whereas Seder\u2019s work required him to custom build a portable ultrasound machine to examine horses, wearable fitness trackers<\/a> and smart exercise equipment<\/a> now allow many users to turn their bodies into data on a daily basis. Privacy experts have raised concerns over this trend, pointing out that these kinds of fitness products can record your biometric data,  location, behavior patterns, and even your face and voice. In one notable case, maps based on Fitbit data revealed the location and layout of US military bases<\/a> around the world and even showed the identities and workout routes of individual soldiers.)<\/p>\n\n\n\n

Stephens-Davidowitz also argues that images can be data. <\/strong>For example, he describes how a company called Premise uses smartphone photos of things like gas station lines or grocery store produce to make economic predictions that are better and timelier than any traditional measures. What both images and biometric data have in common is that they\u2019re easier to collect, compile, and study than ever before. Premise\u2019s work is possible only thanks to smartphones, which guarantee that many people have high-quality cameras on their person at all times and which make it easy to share photographic data to a main hub from anywhere in the world.<\/p>\n\n\n\n

(Shortform note: Whereas Premise contributors collect image data deliberately, other sources of image data are less obvious\u2014and potentially more problematic. For example, Amazon\u2019s smart doorbell Ring has come under fire for sharing video information<\/a> with law enforcement without warrants. Similarly, a British judge recently ruled that a Ring doorbell violated a neighbor\u2019s privacy<\/a> due in part to its ability to record private conversations up to 68 feet away<\/a>.) <\/p>\n","protected":false},"excerpt":{"rendered":"

What types of information does big data provide? How does it get this information? In Everybody Lies, Seth Stephens-Davidowitz says big data opens our eyes to new types of information that weren\u2019t previously available. We can find this new information from search engines and unconventional data sources. Keep reading to learn where this big data information comes from.<\/p>\n","protected":false},"author":14,"featured_media":4843,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[160,25],"tags":[691],"class_list":["post-73009","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-statistics","tag-everybody-lies","","tg-column-two"],"yoast_head":"\nHow Big Data Provides New Information - Shortform Books<\/title>\n<meta name=\"description\" content=\"Big data is able to give us new information we never had access to before. 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