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The Bestseller Code

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G the words alone not just why genre writers like John Grisham and Danielle Steel belong on the lists but also that authors such as Junot Diaz Jodi Picoult and Donna Tartt had tell tale signs of success all over their pages?Thanks to Jodie Archer and Matthew Jockers the algorithm exists the code has been cracked and the results bring fresh new insights into how fiction works and why we read The Bestseller Code offers a new theory for wh This book ended up being even amazing than I expectedThe authors are both literarypublishing experts and have worked on machine learning for years They fed 5000 books published over the past 30 years to their computer programs 500 of those were NY Times bestsellers and the rest weren't They had programs that analyzed for each book the themes and topics ups and downs of the plot characters and the style They had an in sample 10% of bestsellers and 10% of non bestsellers that was used to train their programs and then they forecasted how likely the out of sample books were going to be bestsellersThey were right about 80% of the timeHow did they do it and what are some of the conclusions? I won't spill all the beans but here are some examplesThey analyze topics by looking at nouns that are close to each other So if beer and coctail are near bar the computer concludes the book is talking about a bar in which people drink rather than a bar exam taken by lawyers or a bar used to do pull ups You can see the complexity here the computers have to get the meaning like people from contex in order to learn to read but that's only the first stepThen they looked at hundreds of topics such as guns or health emergency or sex across their sample of books to see which topics were used by the bestsellers and which ones weren't The same for non bestsellers They noticed that sex doesn't sell for instance In addition the number of topics and how often a topic appeared were even important ie a book shouldn't try to cover too many topics How about the plot? They looked at words that showed character feelings to determine whether good or baddangerous things were happening to the characters The cumulative effect is a curve that shows ups and downs of the plot the emotional plotline You want to see curves of course Two winners in this chategory were the two best selling adult books in the last thirty years the Da Vinci Code and the Fifty Shades of Grey CoolThe next big thing is characters To figure them out you want to see what they say think and do The authors accomplished that by analyzing verbs The conclusion is that active characters are better than passive no surprise there Verbs like need and want are much better than wish Lastly there is no good book without a good writing style Even fewer surprises there Basically what the books on writing and editing teach truly works use contemporary language contractions like wouldn't shorter sentences etc I have listed a few examples here There's a lot in the book One interesting thing is their models told them fantasy and science fiction don't work People like to be in our world At first I felt no way but 1 the authors analyzed only books for adults fantasy and scifi totally rule YA 2 many fantasy books happen in our world or have connections to it and 3 you can still pull it off if you do a great job with the plot and the characters like RR Martin I highly recommend this book EnjoyPS The last chapter is uite interesting too So if you can teach computers to read books and make conclusions about them can you teach them to write? It seems we are still in the very early stages of that But it'll happen some day with artificial intelligence I think we are still ways off from that

characters Æ PDF, DOC, TXT or eBook ¸ Jodie Archer

Y Fifty Shades of Grey sold so well It sheds light on the current craze for dark heroines It reveals which themes tend to sell best And all with fascinating supporting data taken from a five year study of 20000 novels Then there is the hunt for “the one” the paradigmatic example of bestselling writing according to a computer’s analysis of thousands of points of data The result is surprising a bit ironic and delightfully unorthodox Did they get high and write this?Jesus This could've been so much better They had all of this great data and then just dragged the fuck out of every chapterand when the actual date was presentedit was fast and in clumps of undecipherable paragraphsGreat Discoveries Horrific Presentation And suck ass drag on writing The Wild West the current craze for dark heroines It reveals which Aramaic Light on Genesis themes Souichis Diary of Curses; 双一の呪い日記; Sōichi no Noroi no Nikki tend درد زمانه to sell best And all with fascinating supporting data Early Medieval taken from a five year study of 20000 novels Then Freakshow there is Pompeii at Dusk (Fresco Nights saga Book 2) the hunt for “the one” Escape from Kathmandu the paradigmatic example of bestselling writing according Talked to Death to a computer’s analysis of More Relaxing, Less Taxing thousands of points of data The result is surprising a bit ironic and delightfully unorthodox Did Diana Palmer Duets, they get high and write Escape From Kathmandu this?Jesus This could've been so much better They had all of Alongshore this great data and The Easter Witch then just dragged How do i Delete Books on Kindle: The Picture Step by Step Guide on How to Remove Books from All Kindle Devices in less than 5 minutes for Complete Novice the fuck out of every chapterand when Mary Coin the actual date was presentedit was fast and in clumps of undecipherable paragraphsGreat Discoveries Horrific Presentation And suck ass drag on writing

Jodie Archer ¸ 4 Free download

Ask most people about massive success in the world of fiction and you'll typically hear that it's a game of hazy crystals balls The sales figures of E L James or Dan Brown seem to be freakish random occurrences in an unknowable market So often we hear that nothing but hype explains their success but what if there were an algorithm that could reveal a secret DNA of bestsellers regardless of their genre? What if it knew just from analyzin There's an observation that sometimes goes around about how you only need to read the fourth chapter of any given business book The first is an introduction the second is about how everything you thought you knew about the subject was wrong the third is the miraculous tale of how the authors came up with this new secret answer and the fourth is the actual content After that it goes into testimonial style case studies and other rather dull stuff So the fourth chapter or sometimes I've heard the fifth is the only one you need to pay attention to Either way the point is that there's a certain class of non fiction book that's mostly padding with an article's worth of actual content The Bestseller Code Anatomy of a Blockbuster Novel felt like one of those books to meThe Bestseller Code's been modestly controversial since it's publication either because it's heretical to declare that there's a machine identifyable set of characteristics to making a bestseller or because everyone already knew what those characteristics were so who needed the computer? I tend to disagree with both critiues First of all if software can identify the patterns that lead to success then better we become aware of it than pretend the publishing business is driven entirely by artistic impulse Second if such a secret cluster of characteristics exists then the monumental pile of unsuccessful novels that come with major publisher backing is evidence that most people in the industry don't know what they areThe problem is that The Bestseller Code isn't really going to show you one way or another because while the book repeats the same mantra over and over and over that our model predicted bestsellers within our sample with 80% accuracy there's actually very little evidence given The data isn't there for one to consider nor is the entire list of topics nor their full rankings within the model So while I've no doubt that the authors successfully built a set of algorithms to measure a given text's likelihood of hitting a bestseller list slogging through their 240 page advertisement for it is a pretty unsatisfying read There just isn't a lot of detail or actual information on offer Sure there are a few generalizations write short simple sentences with lots of contractions that deal as much as possible with the topic of human connection and if you can get I and him in close proximity your on the right track but they're precisely the ones you'll find brought up everywhere Such sage advice as sticking to no than three main topics in your book and not over writing your sentences doesn't reuire an algorithm – you hear it all the timeSo the problem isn't that the authors are wrong or haven't discovered something intriguing – and perhaps extremely useful – about the nature of bestsellers; the problem is that they really aren't sharing much of it in this book That's a logical tactical choice if you plan on going into the business of getting people to pay you to run their books through your software but it doesn't make The Bestseller Cods Anatomy of a Blockbuster Novel a very useful or engaging read


10 thoughts on “The Bestseller Code

  1. says:

    I honestly thought I would enjoy this book than I did Part of the problem might have been the not so secret snobbishness I have when it comes to bestselling novels There's a little voice in my head that tells me that if a book appeals to the masses it's probably not going to do much for me And in most cases that's true I don't very often read titles that make the lists and when I do it's usually by accident or if the book has been chosen by my book club I've never read anything by Dan Brown Jodi Picoult or James Patterson And no I've never read Fifty Shades of Grey There is some interesting information here but it does tend to get repetitive I had the feeling I so often get when reading nonfiction that the contents could have easily been covered in a magazine article The facts I found most interesting were that a novel's first sentence is freuently an indicator of its possible financial success that a computer rightly deduced Robert Galbraith was actually JK Rowling and that out of all the bestselling authors John Grisham and Danielle Steel hit the right buttons than any other writers It should be noted there are a lot of spoilers; plots and endings of many bestsellers are discussed in great detail On the plus side anyone who's fond of charts and graphs should be delighted by this book Personally I think the data discovered will appeal to writers than readers I much preferred a fiction book I read recently on this same subject How I Became a Famous Novelist That one I would recommend


  2. says:

    There's some good advice in here even if it mostly feels kind of icky Mostly it's a commercial for the services the authors offerBut I did learn a few things So that's goodI guess someday if when??? I get a seven figure advance and become the new JK Rowling I'll change this to five stars Ha


  3. says:

    There's an observation that sometimes goes around about how you only need to read the fourth chapter of any given business book The first is an introduction the second is about how everything you thought you knew about the subject was wrong the third is the miraculous tale of how the authors came up with this new secret answer and the fourth is the actual content After that it goes into testimonial style case studies and other rather dull stuff So the fourth chapter or sometimes I've heard the fifth is the only one you need to pay attention to Either way the point is that there's a certain class of non fiction book that's mostly padding with an article's worth of actual content The Bestseller Code Anatomy of a Blockbuster Novel felt like one of those books to meThe Bestseller Code's been modestly controversial since it's publication either because it's heretical to declare that there's a machine identifyable set of characteristics to making a bestseller or because everyone already knew what those characteristics were so who needed the computer? I tend to disagree with both critiues First of all if software can identify the patterns that lead to success then better we become aware of it than pretend the publishing business is driven entirely by artistic impulse Second if such a secret cluster of characteristics exists then the monumental pile of unsuccessful novels that come with major publisher backing is evidence that most people in the industry don't know what they areThe problem is that The Bestseller Code isn't really going to show you one way or another because while the book repeats the same mantra over and over and over that our model predicted bestsellers within our sample with 80% accuracy there's actually very little evidence given The data isn't there for one to consider nor is the entire list of topics nor their full rankings within the model So while I've no doubt that the authors successfully built a set of algorithms to measure a given text's likelihood of hitting a bestseller list slogging through their 240 page advertisement for it is a pretty unsatisfying read There just isn't a lot of detail or actual information on offer Sure there are a few generalizations write short simple sentences with lots of contractions that deal as much as possible with the topic of human connection and if you can get I and him in close proximity your on the right track but they're precisely the ones you'll find brought up everywhere Such sage advice as sticking to no than three main topics in your book and not over writing your sentences doesn't reuire an algorithm – you hear it all the timeSo the problem isn't that the authors are wrong or haven't discovered something intriguing – and perhaps extremely useful – about the nature of bestsellers; the problem is that they really aren't sharing much of it in this book That's a logical tactical choice if you plan on going into the business of getting people to pay you to run their books through your software but it doesn't make The Bestseller Cods Anatomy of a Blockbuster Novel a very useful or engaging read


  4. says:

    This book ended up being even amazing than I expectedThe authors are both literarypublishing experts and have worked on machine learning for years They fed 5000 books published over the past 30 years to their computer programs 500 of those were NY Times bestsellers and the rest weren't They had programs that analyzed for each book the themes and topics ups and downs of the plot characters and the style They had an in sample 10% of bestsellers and 10% of non bestsellers that was used to train their programs and then they forecasted how likely the out of sample books were going to be bestsellersThey were right about 80% of the timeHow did they do it and what are some of the conclusions? I won't spill all the beans but here are some examplesThey analyze topics by looking at nouns that are close to each other So if beer and coctail are near bar the computer concludes the book is talking about a bar in which people drink rather than a bar exam taken by lawyers or a bar used to do pull ups You can see the complexity here the computers have to get the meaning like people from contex in order to learn to read but that's only the first stepThen they looked at hundreds of topics such as guns or health emergency or sex across their sample of books to see which topics were used by the bestsellers and which ones weren't The same for non bestsellers They noticed that sex doesn't sell for instance In addition the number of topics and how often a topic appeared were even important ie a book shouldn't try to cover too many topics How about the plot? They looked at words that showed character feelings to determine whether good or baddangerous things were happening to the characters The cumulative effect is a curve that shows ups and downs of the plot the emotional plotline You want to see curves of course Two winners in this chategory were the two best selling adult books in the last thirty years the Da Vinci Code and the Fifty Shades of Grey CoolThe next big thing is characters To figure them out you want to see what they say think and do The authors accomplished that by analyzing verbs The conclusion is that active characters are better than passive no surprise there Verbs like need and want are much better than wish Lastly there is no good book without a good writing style Even fewer surprises there Basically what the books on writing and editing teach truly works use contemporary language contractions like wouldn't shorter sentences etc I have listed a few examples here There's a lot in the book One interesting thing is their models told them fantasy and science fiction don't work People like to be in our world At first I felt no way but 1 the authors analyzed only books for adults fantasy and scifi totally rule YA 2 many fantasy books happen in our world or have connections to it and 3 you can still pull it off if you do a great job with the plot and the characters like RR Martin I highly recommend this book EnjoyPS The last chapter is uite interesting too So if you can teach computers to read books and make conclusions about them can you teach them to write? It seems we are still in the very early stages of that But it'll happen some day with artificial intelligence I think we are still ways off from that


  5. says:

    Using a computer algorithm the authors of this book as the uestion of whether you can predict whether a novel will be a bestseller or not Jodie Archer is a former publisher and consultant while Matthew Jockers is the co founder of Stanford University’s famed Library Lab In this work they claim they can discover a bestseller and analyse 20000 novels to demonstrate thisSubtitled “Anatomy of the Blockbuster Novel” this book attempts to analyse novels from the points of view of theme plot style character and all data points Of course much of this is fairly obvious as are the results of computer generated writing For if a computer can analyse what works within a novel why can they not write that elusive bestseller?Overall this is an interesting looks at the mechanics of writing and publishing our obsession with lists and ranking and the anatomy of what creates a perfect story The book also contains a list of 100 novels it believes you should read – as an avid reader I have read only six of them and the books which are missing include every classic However as the title suggests this algorithm aims to discover that bestseller – the book that is in every supermarket and is the talked about novel for a certain amount of time Some may become classics others may not wear as well and that is why thankfully literature is based on than commercial success An interesting exercise though and a fun analysis of the bestseller charts


  6. says:

    The title of this book has it all for meit's the reason I picked it up in the first place The idea that blockbuster novels all share some elemental DNA in common is at once exciting and dangerousI found that the authors of this book set out to prove their algorithm without giving away too many of the intricate details likely proprietary information and for the most part made their case in a concise and believable mannerFor the most partI honestly would've liked to have seen actual numbers produced from their research contained within the pages of this book For budding novelists out there let me spare you the time; this book will not deliver that one crucial element or secret to you that will make you a bestseller It will get you looking at the number of times you use the word the and how often you use pronouns or Mr King's dreaded ly words It will tell you how bestselling authors writeor it will try to tell youAt the end of the day the machine can data mine thousands of best sellers but in my opinion never uncover the secret sauce Talent with words goes beyond their placement within a sentence of the size of one's paragraphs What all best sellers really have in common is a love of language and a love of writingAnd I've yet to come across the machine that can understand thatyet ;


  7. says:

    Recommending a book is not like recommending a health tip or a stock Recommending a book can be like trying to navigate the unspoken rules and faux pas of a Jane Austen ballroom The book world comes with considerable baggageWho can explain what makes for a best selling book? What techniues do best selling authors employ that makes their works so desirable compared with the majority of authors who struggle for readership? Do those who write literary classics differ so much from those who appeal to the mass market?All this and is covered in this fascinating look at big data and the New York Times best seller list There are actually two fascinating parts to the book The first part covers the actual results of the study that is what makes for a best seller? Second and eually interesting is how the big data on books are collected and interpreted A side look at the interests and predispositions of readers at both the literary and mass market levels are fascinating as well Who among literary lovers has not succumb to a mass market book despite their professed inclination otherwise? For example I count Dan Brown and The Da Vinci Code as among my particular weaknesses although I don't usually find what I'm going to read from among the typical household names on the best seller listIs that unnecessarily snobbish? Am I no better than a fashionista who refuses to wear anything without a Prada or Hermes label? Or a foodie who refuses to eat anything that isn't farm to table? Book people to thine own self be true Those best sellers are popular for a reason and the best selling formula can truly be seen on display here It's a fascinating look too at why machines can't at least not yet replace writers despite all that they can do otherwiseThere's so much to think about in this short bookas well as plenty of reading suggestions for those book list compilers It demonstrates very well what big data has yet to teach us about so many things beginning with one of our favorites what we readMy thanks to Good Reads and St Martin's Press for allowing me to read this book


  8. says:

    Did they get high and write this?Jesus This could've been so much better They had all of this great data and then just dragged the fuck out of every chapterand when the actual date was presentedit was fast and in clumps of undecipherable paragraphsGreat Discoveries Horrific Presentation And suck ass drag on writing


  9. says:

    I found this book fascinating reading The authors wrote a computer programme which could read and analyse books and this is the result They wanted to see if a computer could predict which books would be best sellers and which wouldn't A lot of the time it got things right but with some books it was completely wrong stating that a book was unlikely to be a best seller when it was actually a blockbuster I thought it was interesting that a computer could tell whether it was a man or a woman who had written a book and whether two completely different books were written by the same person Robert Galbraith and J K Rowling were easily identified as the same person by the computer Best selling books use verbs and fewer adverbs and adjectives and concentrate on a small number of themes for thirty percent of the book apparently Best selling authors use contractions such as don't won't she's he's etc Whether or not you habitually read best selling fiction this book provides some fascinating insights into the way best sellers grab the public imagination and sell millions of copies across the world If you're worried that the book will go into too much detail about the way the computer programme works then rest assured this detail is kept to footnotes and a section at the end The text is mainly about the insights provided into the way best sellers work The book has certainly made me look at best sellers differently and I might actually go on to read of themThe book provides a list of the computer's top one hundred books if you want to start reading all those block buster books you've missed The authors really bring their subject to life and I liked their touches of humour and the descriptions of the difficulties they had in getting the computer to understand nuances which human readers take for granted I loved the irony of the choice the computer made for its favourite book which caused me to wonder what the computer would make of Jane Austen that master of irony It also made me wonder whether a sense of humour could be programmed into a computer


  10. says:

    Despite all the efforts of publishers it has always seemed impossible to predict whether or not a book would be runaway bestseller This isn't too surprising it's the kind of thing that is inherently unpredictable because there are simply so many variables involved Yet a newly published book suggests it is possible to do just that Are the authors crazed or brilliant? Neither really They have put together a mechanism based on computerised text analysis that is good at spotting bestsellers and yet oddly this doesn't contradict that inherent unpredictability Why? Because there are two different levels of bestsellerdom involved and because I think there's one bit of information missing from the book apologies to the authors if I've missed itSo what does the software do? By looking at various word uses patterns and shaping it can make a good shot at predicting whether or not a book is likely to have featured on the New York Times bestseller list This is very impressive and along the way Jodie Archer and Matthew Jockers give some excellent advice on things that authors can do or at least try to do that will make their books like these bestsellersThis isn't a universal panacea In fact the authors admit that what their algorithms spot is not what most would regard as great fiction The system laps up the like of the output of Dan Brown and 50 Shades of Grey But interestingly it also is useful counter to those who say they can't understand why these kind of books sell because they are terribly written In fact in a number of respects these books are very well written it's just that the criteria for 'well written' are not those used by the lit crit brigadeNot only is this not a recipe for producing great literature it's not about producing books everyone would like either Taking a uick skim through the top 100 books selected by the analysis there are perhaps three I would consider reading But many of us are not 'bestseller' readers We like our own little niches and that's fine This system isn't for us it is about finding likely hits for the traditional bestseller marketThis genuinely is all very interesting although the book has surprisingly little content for a full price hardback it's large print and there's a lot of dancing around exactly what they are doing However what absolutely isn't true is the assertion made here that 'mega bestsellers are not black swans' The system uses a number of measures and though it's true that most mega sellers like Harry Potter and 50 Shades do well on some of the measures they pretty well all fall down on others So for instance to write a bestseller we are encouraged to avoid fantasy very British topics sex and descriptions of bodies What the model seems to do well is to recognise what you might call the run of the mill bestsellers rather than pick out most of the real runaway successes as being stand outThere was also that missing bit of information The authors are enthusiastic to tell us how many books that scored highly from their system were on the bestseller list and that really is impressive But they don't mention false positives how many books the system thought should be bestsellers but weren't That would have been interesting to discover aboutI'm sure we'll hear of this kind of analysis but I really hope publishers don't put too much stock by it because it is very much a lowest common denominator approach certainly from the viewpoint of someone who wouldn't consider reading than 95% of their recommendations That's not to say that the book isn't interesting and for an author there are some excellent insights into some of the things that attract this generic group of readers or put them off that are worth considering even if you do write science fiction or British crime fiction sayA fascinating piece of analysis provided you don't take it all too seriously


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