๐ Founder @Geospatial Data Consulting | ๐ฅ๏ธ Data Scientist | ๐ฏ PhD in Network Science | ๐ Author | ๐๏ธ Forbes 30u30
The data book of the week is ๐๐ง๐๐ก๐๐ซ๐ญ๐๐: ๐๐ข๐ ๐๐๐ญ๐ ๐๐ฌ ๐ ๐๐๐ง๐ฌ ๐จ๐ง ๐๐ฎ๐ฆ๐๐ง ๐๐ฎ๐ฅ๐ญ๐ฎ๐ซ๐ by ๐๐ณ๐ฆ๐ป ๐๐ช๐ฅ๐ฆ๐ฏ and ๐๐ฆ๐ข๐ฏ-๐๐ข๐ฑ๐ต๐ช๐ด๐ต๐ฆ ๐๐ช๐ค๐ฉ๐ฆ๐ญ. The authors studied millions of books digitalised by the #GoogleBooks product. This itself has been a very interesting case about data usage and copyright legislation, though, so eventually, they did not directly look into the complete texts of the books. Instead, they organised the world into alphabetical orders and counted them in different ways - creating so-called n-grams. A byproduct of the research is this searchable online tool as well many of you have probably seen already: https://lnkd.in/dwek6ZmQ Besides, the book has several curious findings and enlightening stories: โ For one, on language evolution. We probably all knew already - and not known - that there are quite a few irregular words in English which, when put into a past tense, donโt get the -ed ending described by the rule but have some other weird forms. They traced down 177 irregular words in Olg English (9th century) and then scanned through all the books digitalised by Google century by century. In the end, they saw that todayโs English only has 98 of those irregular words - the rest regularised and got the -ed ending. The trick comes here: the lower more frequent a word is, the less likely it will get regularised, implying that the language evolution of irregular words is pressed by their frequency. The more frequent, the harder to change. As the language evolves, the authors say that by 2500 there will be only 83 irregular words, and it's still about 7800 years since drove becomes "drived".โจ โจ โ They studied the fame of people based on the number of times their names were printed in books. Then compared fame to the profession. Turns out, if you want to be famous and achieve that while still young - become an actor! Contrasting to quick fame, writers become increasingly famous as they age - eventually topping actors. So do politicians whose careers hit the peak in their 50s and 60s, also much higher than that of actors. And, if you really want to be famous - donโt become a scientist! They reach about the same level as actors - but most likely by their 60s, taking twice as much for them than for actors. โ Based on the frequency of specific terms and n-gram in books, they studied how we collectively forget. They benchmarked this quite brilliantly by counting how many times each year was mentioned - like 1864 or 1915. When a specific year comes, the interest spikes then drops to half in a few decades and starts to decay exponentially. We forget fast, and older things are being forgotten ever quicker! #dataviz #datavisualization #data #datafam #datascience #bookaweekchallenge #book #bookreview #datascience #dataliteracy #networkscience #datastories #ai #chatgpt #nlp #languageprocessing #naturallanguageprocessing โจ
