[HN Gopher] I Want to Fix Goodreads
___________________________________________________________________
I Want to Fix Goodreads
Author : prepend
Score : 143 points
Date : 2020-09-12 18:06 UTC (4 hours ago)
(HTM) web link (prepend.com)
(TXT) w3m dump (prepend.com)
| Nemo_bis wrote:
| There are many Goodreads competitors. To the others already
| mentioned, I'll add https://inventaire.io/ , which is fully free
| software and based on open data (Wikidata).
|
| It's useful if you want to have full control on your own book
| catalogue while not having to produce all the data yourself.
| michaelmrose wrote:
| Is the recommendation engine bad on average or bad for you?
| Minor49er wrote:
| One thing I'd add about the UX is that the search bar is buried
| below the fold on the homepage of the desktop version. Everywhere
| else, even on mobile, it's at the very top. It makes it a little
| more difficult to just jump to their site and start searching.
| hganesan wrote:
| I've been building a prototype over at https://longtweetsapp.com
| because I've had the same problems. It's hard to find books so I
| took a more personalized, data-driven approach, starting with
| Twitter networks, because I was tired of bestseller and most
| popular lists.
|
| It's still early goings, but I'd love feedback - I'm dogfooding
| it with interesting results. Send me a note:
| hareesh.ganesan+longtweets@gmail.com
| vhpoet wrote:
| I'm trying to tackle a small part of this by building
| https://www.readthistwice.com which gives contextual
| recommendations from 1300+ leaders. What I mean by contextual in
| this case is every recommendation comes with a verified quote
| from the recommender on why they recommend the book.
| paxys wrote:
| Book rating and recommendations are an impossible problem to
| begin with. If you browse through Goodreads, you will see that
| _everything_ is rated 4 stars. People only finish and rate books
| they like, and it 's impossible to compare books of different
| genres, lengths, time periods, complexity etc. on the same
| objective scale like it is for movies or TV shows.
| DavideNL wrote:
| Fun fact: for like 2 years long, every time i opened
| Goodreads.com i saw the exact same sentence: _" Because Deborah
| liked.... she discovered...."_
|
| The exact same books/text for about 2 years. Torture...
| YetAnotherNick wrote:
| Isn't it the same problem with Amazon? It shows me different
| versions of the 5 products I last viewed. And unlike, goodreads
| it seems like there is clear monetary value for amazon in fixing
| product recommendations but somehow it is the same for years.
| alehul wrote:
| > I wish there was some way to note books that I don't want to
| read.
|
| Minor point but there is a "Not interested" button in the
| screenshot shown above this paragraph. While Goodreads' initial
| suggestions were off-the-mark, I wonder if using that would help?
| viiralvx wrote:
| A buddy of mine has started on a better designed alternative to
| Goodreads. It's in early access right now but it has potential
| and I'm looking forward to seeing what else he adds to it:
| https://readng.co
| buovjaga wrote:
| There is at least https://gitlab.com/Alamantus/Readlebee "An
| attempt at a viable alternative to Goodreads", in active
| development.
|
| Blog post from yesterday:
| https://robbie.antenesse.net/2020/09/11/one-year-of-readlebe...
|
| Edit: oh, there is also Bookwyrm, as mentioned in this megalist:
| https://git.feneas.org/feneas/fediverse/-/wikis/watchlist-fo...
| nonbirithm wrote:
| How do people build recommendation engines?
|
| Like, even when you have access to the site's entire API and can
| write your own client for it, there's still the fact that their
| recommendations are generally better.
|
| It sounds like an extremely important value-add. There are many
| sites that I will only use the app for because that is where the
| recommendations are shown. But to me taking a user profile and an
| article and spitting out a list of articles seems like magic.
|
| I also find it weird that in 2020 Goodreads is the status quo for
| book recommendations.
| searchableguy wrote:
| The best recommendation engine is other people that you know
| and understand.
| gbtw wrote:
| > How do people build recommendation engines?
|
| Poorly, its either shovel so much shit against a wall to see
| what sticks (youtube) or you sorta watched this for 10 minutes
| to see if you liked it but you didn't but here is more
| (netflix).
|
| Curated lists made by humans are still nicer.
| hazard wrote:
| It's not that hard. See for instance
| https://www.coursera.org/lecture/machine-learning/collaborat...
| on how to get started
| dtech wrote:
| It's not hard to build something that gives you
| recommendations. It extremely difficult to build something
| that works well. For consumer companies I know only Spotify
| and TikTok that do it well, and Youtube that does it OK-ish.
| moltar wrote:
| I personally wouldn't say that Spotify does it well. I
| don't think I've ever gotten a good recommendation. And
| daily playlists are a mess.
| nelsondev wrote:
| > How do people build recommendation engines?
|
| One method, collaborative filtering with latent factor
| analysis, popularized by its efficacy in making recommendations
| on Netflix, is to use matrix multiplication to solve the
| problem.
|
| E.G. Let's say you have all users (rows) x all books (columns),
| in a massive sparsely populated matrix, where the value is the
| rating that user gives a book.
|
| To make recommendations, the goal is to "guess" what a user
| would rate a book they haven't read, and if your guess is they
| would give it 5 stars, and then you recommend it, and the user
| gives it 5 stars, it's a good recommendation.
|
| The "latent factor" idea is breaking the problem up, so in
| order to compute the rating matrix that is the final size N
| users by M books, you split it into:
|
| N users x D latent factor (cross product) D latent factor x M
| books = N users x M books
|
| It then becomes a machine learning problem, using a loss
| function plus gradient descent, to solve for that D latent
| factor.
|
| Customers with a similar latent factor, will have similar
| taste.
|
| Once you have the latent factors, you find the nearest
| neighbors (the closest other latent factor vectors measured by
| dot product or cosine similarity), to compute the nearest
| books. The vectors that multiply together to give the highest
| rating, will be the best recommendations for the user.
| prepend wrote:
| For me, I only use goodreads because there's nothing better
| that I've found. I think of it as similar to evolution,
| evolution is just about survival, not necessarily the best at
| stuff that's not survival.
| DominikPeters wrote:
| There's an entire research field about Recommender Systems
| (https://en.wikipedia.org/wiki/Recommender_system) with its own
| conference series (https://recsys.acm.org/).
| krrishd wrote:
| I get the sense that part of the problem with book recs vs.
| YouTube video recs is that you can evaluate the quality of a
| video recommendation super quickly (click in, find out like 10
| seconds in that you don't care for it, click out).
|
| With books, actioning a recommendation involves
|
| 1) getting a copy of the book (digital or physical, both cost
| money or at minimum the time required to pirate),
|
| 2) starting to read it (with the sunken cost of time and/or
| money + the drive to "give it a chance" both looming over your
| shoulder, costing you more time),
|
| 3) eventually either getting to the end or swallowing your
| pride and bailing.
|
| I think you'd start to see actually useful systems here if you
| could even eliminate step 1; make it easy as clicking in from a
| recommendation directly into reading mode.
|
| Also solves a critical issue for the engine: gauge
| recommendation quality by how soon people click out of the rec,
| as opposed to waiting for the user to go through steps 1-3, and
| care enough to come back and provide a rating. Way more data to
| work with.
|
| Of course, this all skirts the Actual Problem: the amount of IP
| law you'd have to trudge through in making enough books this
| accessible.
| krrishd wrote:
| I also recently googled a quote, found it in a specific page
| in a book hosted on https://www.pagebypagebooks.com/, and
| just impulsively clicked through the whole book because it
| happened to capture my interest, and only "demanded" that I
| commit to a single page at a time. Hard to explain, but it
| felt more natural in that every-page-is-a-URL format to
| trivially bail at any page, without the weird apprehension I
| get from the same action in an e-reader / physical book.
|
| The website is super old/limited, but if all books were that
| trivial to access + click through, I think we'd see something
| more interesting here. Made me wonder how hard it'd be to
| convert the entirety of Project Gutenberg into that sort of
| Web 1.0 format automatically.
| munificent wrote:
| _> They recommend different versions of books I've read. They
| recommend two different versions of Lord of the Rings (one of my
| favorite books), but I guess they don't know these are the same
| book._
|
| This is failure mode of recommendations is so common and so
| catastrophically useless that I do not understand how it has not
| been solved.
|
| I'm into photography, so every now and then I buy a lens from
| Amazon. Immediately after I do, every Amazon ad banner on every
| website in the world switches to advertising that specific lens,
| for like the next month (I guess until I buy something else).
|
| Lenses are very specific, expensive, and singular. There is
| almost no reason to ever have two of the same lens. The day after
| I buy a lens, it is practically the least likely product _in the
| world_ that I will buy.
|
| Show me anything but that. I mean, actually, don't. I like this
| failure mode because it makes it easy to tune out the ads. If
| they showed me related gear (perhaps filters that fit the lens),
| I might get suckered into spending more.
|
| But, seriously, how is this not fixed?
| shostack wrote:
| One of the best parts of Goodreads for me is the Listopia search.
| Regular search doesn't get me much, but this search is fantastic
| for going really niche on certain topics.
| mmanfrin wrote:
| My wish: show me all the books my friends have reviewed, and
| allow me to sort by number of reviews. I want to see what a
| _plurality_ of my friend recommend.
| giberson wrote:
| > My idea for an 11-star experience 1 in finding new books is
| that Goodreads knows me even better than I know myself and
| constantly recommends the perfect book.
|
| > goodreads shows me five books that I don't want to read.
|
| I wonder if these two ideas are at odds with each other. Imagine
| for a moment that recommendation engines were solved problems,
| and definitely worked given the above statement. They know you
| better than you know yourself. Would it's recommendations likely
| only include books that you obviously wanted to read? Or would
| they include books you didn't know you wanted or needed to read?
| I mean this in terms of judging the books by their cover rather
| knowing about their existence. Isn't it likely or even probable
| that the majority of books recommended would be based on the
| value they contribute to something deeper than the pure enjoyment
| purposes?
|
| As an aside, I remember in a college literature class I took the
| instructor told us that it's up to the reader to derive value or
| meaning from stories. This was a class that studied short stories
| of early American authors. Most of which were slice of life
| narratives that didn't have any apparent meaning, or commentary
| from the authors themselves. The exercise was to study the
| characters, scenery and tone and try derive what might either lie
| beneath the words or story themselves. Whether the ideas we
| deduced from the stories were accurate (and in most cases
| probably were not) the value Of the process was of critical
| thinking about the stories that made us consider and express
| ideas and beliefs we normally don't.
|
| Back on topic, would a working recommendation engine likely
| suggest things that on the surface seemed either boring or
| blatantly unappealing that would provide tremendous value if we
| put work in to reading and studying?
|
| That being said, is it possible that current recommendation
| engines are already working? Most are at least driven by reading
| behaviors of the masses, so it seems like it might be feasible
| that that Steven king book that is unappealing to you is
| something you should actually read.
|
| (This is not including recommendations for books you have already
| read in different languages which seems like an obvious bug, but
| then again reading books you've already read in different
| languages might be an excellent way to become more fluent in a
| new language or gain a deeper understanding of translation of
| ideas between languages....)
|
| So, maybe the tech isn't something that needs to be fixed. Maybe
| we just need to be open to what the tech is telling us?
| matsemann wrote:
| I think you are right. Being recommended a book I've never
| heard about by some author I'v never heard of by some computer
| system, I'm probably gonna dismiss it. However, if I've seen it
| in a bookstore, read about it in a paper, heard a friend talk
| about it etc. _then_ I might act on the recommendation.
|
| Basically being exposed to something enough times. First time
| and a cursory look, most things don't look to exciting. This
| goes for everything. Movies, restaurants, gadgets..
| esquire_900 wrote:
| After reading and heavily agreeing with this post, I came to the
| conclusion that either goodreads is not really trying, or -more
| likely- the data is just not good enough to make decent
| recommendations. There are so many biases in the review data that
| are impossible to fix in any kind of sparse matrix recommendation
| algorithm. For those who want to try anyway, it might be worth
| downloading an existing dataset (1) (104 million reviews) and
| try, before worrying about scraping and api limits.
|
| The only solution (in my experience) is to get some other way of
| quantifying content, like Spotify does by manually labelling
| tracks. After some ddg I found storygraph (2), which does this.
| Its search engine is quite impressive, might be worth trying.
|
| [1] https://sites.google.com/eng.ucsd.edu/ucsdbookgraph/home [2]
| https://beta.thestorygraph.com
| kobe_bryant wrote:
| the problem is that when you step out of genre fiction, you
| cant just recommend a book with a similar plot or setting, it
| needs to have a similar style of writing and sensibility and
| thats very hard to determine.
|
| the best way is friending/following people and learning their
| tastes compared to yours
|
| e: if you go to a specific book and look up similar books,
| goodreads actually does a pretty good job
| https://www.goodreads.com/book/similar/1994351-j-r
| anonreader123 wrote:
| I am a Goodreads employee. this is a burner account. i could be
| fired for posting.
|
| we love Goodreads and we know it is bad today. we are working to
| fix it. there are very few of us. we are trying. we are making
| big changes soon.
| JesseMReeves wrote:
| Happy to read that you are working on improvements! GoodReads
| is my most-used and most important database. I love it, I also
| actually like that it feels more like an "older" webpage before
| all this craziness with stealing the attention and time of
| users came up (Goodread in its current state is already
| addictive enough for me). I hope you fix the bigger issues
| (like slow loading times, recommendations, convoluted UI) but
| keep the aim-at-making-the-page-actually-useful (and not a
| manipulative time sink) approach.
|
| Feature wishes: Extensions on book statistics, a function for
| discovering like-minded users, marking books as ,,finished" /
| ,,decided not to finish" and showing this information (this
| could provide some very useful additional information on
| books), and maybe a ,,listened to the audiobook" marker.
| Shared404 wrote:
| Good luck.
| Paul_S wrote:
| Do you recommend books based on ML or do you hand pick books
| you want to promote because you think they should be promoted
| or have been paid to promote them?
| anonreader123 wrote:
| only ML. no promo -- nothing sneaky -- we hate sneaky
| anaganisk wrote:
| There's an Ex-NSA in the board of Amazon now.
| [deleted]
| jonathanwallace wrote:
| Best of luck and thank you.
| rexpop wrote:
| > i could be fired for posting.
|
| Yikes, that's rather dramatic! Especially since all you've said
| is "we're working to fix it. changes soon." That's a pretty
| harmless statement, I would think.
|
| What gives you the idea that such statements put your
| employment at risk?
| Infinitesimus wrote:
| It might be the general fear present in some Amazon corp
| offices? (PIP stories, etc.)
| rexpop wrote:
| > general fear present
|
| I don't know about this. Is it documented, or have you
| "heard it through the grapevine," so-to-speak?
| toyg wrote:
| _> there are very few of us. we are trying_
|
| This implies support for Goodreads at Amazon is very thin. It
| could be read as a critical statement (even though it's
| pretty clear to everyone that the site very clearly stagnated
| since the acquisition, focusing almost exclusively on Kindle
| integration).
|
| Amazon management is famously militaristic in attitude and
| would likely take action against a low-level employee
| criticizing the company in public
| rexpop wrote:
| > management is famously militaristic
|
| Although I know that Amazon is hiring intelligence
| operatives[0] to bust unions, this aspect (militaristic
| middle management) is news to me. Where can I learn more?
|
| 0. https://www.theverge.com/2020/9/1/21417401/amazon-job-
| listin...
| toyg wrote:
| They have a recruitment scheme directly targeted:
| https://www.amazon.jobs/en-gb/military
|
| I'm pretty sure it was also reported in the past that
| Bezos traditionally favored ex-military for manager
| positions when Amazon was starting, but I cannot find a
| source atm (seems like yesterday to me but more than 20
| years have since passed...).
| sillysaurusx wrote:
| I downvoted you but I feel bad for not explaining why.
|
| One of my memories: Being pulled into a side office and
| grilled for a half hour for posting a similarly harmless
| statement to HN.
|
| So your comment triggered mild PTSD.
|
| It's not your place as an individual employee to post about
| your employer. You work in a team setting. If the team
| decides it's appropriate to post to HN, then that's fine. But
| you alone do not get to decide that.
| paulcole wrote:
| > we know it is bad today
|
| This is the kind of thing companies love their employees to
| share publicly!
| recuter wrote:
| How many of you are there?
| anonreader123 wrote:
| not enough.
| O_H_E wrote:
| My heart by with you fellow human. Thanks for trying to
| make the world a little better even under less-than-ideal
| conditions.
| darkerside wrote:
| What are the most important changes that your team is
| prioritizing?
|
| What are your biggest challenges with making them?
| anonreader123 wrote:
| I want to be specific but I would get fired if they saw. but
| we read EVERY post about us. we are being ambitious and big
| changes are coming.
|
| biggest challenge is there is too much to do and we have so
| few staff.
| acchow wrote:
| How many engineers?
| [deleted]
| darkerside wrote:
| This is so vague that if you're not faking it, you might as
| well be. Sorry, but don't bother posting, even under a
| throwaway, if you're not going to engage.
| immy wrote:
| All it does is discourage timid people from making an
| innovative competitor.
| SECProto wrote:
| Can we have half stars or quarter stars? I read a lot of books,
| and choosing full-star 1 to 5 makes the ratings pretty useless
| for people who read a lot. My internal rankings are:
|
| 1 hated it/was offended/didn't finish
|
| 2 disliked it/likely didn't finish
|
| 3 finished but it was a struggle
|
| 4 finished/enjoyed/had some issues
|
| 5 finished fast/really enjoyed/may or may not have still had
| issues.
|
| If I look back at the 30 to 50 books I read in a year, it's
| really difficult to get any sort of ranking out of them. I've
| only got two choices for books I liked (4 or 5) and two choices
| for books I disliked (1 or 2). Having half stars would help my
| ratings relative to one another.
| heurist wrote:
| I have been rating a year or so after reading based on how
| much of the book I remember or how much it influenced me.
| It's made rating much easier.
| SECProto wrote:
| That doesn't fundamentally change that there are only 2
| choices available for books I've enjoyed.
|
| Also, if you asked me about a book I read a year ago, I
| wouldn't be able to do much more than confirm I read it.
| That's part of why I use Goodreads.
| macobo wrote:
| Why take 60% of the rating space up by negative ratings? It
| seems like what you really care about is degrees of goodness.
|
| An alternative approach:
|
| 1 - I disliked it. 2 - It's OK 3 - This is good 4 - This is
| great 5 - This is a must-read
| dwighttk wrote:
| I don't care about reviews or recommendations. I have a to-read
| list that will last me the rest of my life easily.
|
| The thing I hate about goodreads is there are two search fields
| one to search books you've read and one to search every book.
|
| I've wanted to search books I've read like 5 times in my life but
| for some reason I always end up using the only search books I've
| read search bar and I get no results. Just make it a checkbox or
| return two lists or something.
| 50 wrote:
| Haven't used it myself since it's in beta but I have been keeping
| my eyes on this for a while: https://beta.readng.co/,
| https://twitter.com/readngco
| buttscicles wrote:
| Hi, I'm building this! Thanks for sharing.
|
| It's pretty basic right at the moment and we've a lot left to
| build (largely a reading list only, we've got more in the
| works) - but here's my profile as a preview, since our
| marketing site & messaging needs a bit of work:
| https://beta.readng.co/user/joe
| ibn_khaldun wrote:
| User name checks out. Lots of gratuitous butt-cleavage on the
| site. Looks nice and I am interested. But _why_ all the
| butts?????
| armSixtyFour wrote:
| Goodreads doesn't get enough love from Amazon, It always seemed
| really odd to me that the recommended books in the kindle store
| were better than goodreads even though it's all the same company.
| It seems like a wasted opportunity. There are also numerous bugs
| I've ran into on the app that I just work around.
| johnfn wrote:
| Good lord what I wouldn't give for a better goodreads. Never has
| so much useful and actionable data been squandered. For example,
| I could write pages about how bad the "top books" lists are. The
| Goodreads Choice Awards are purely and literally popularity
| contests, for example. Why would this be the case - you have
| millions of user ratings, you should be using those to surface
| exciting and unknown books rather than throwing people back at
| the same few authors they already know. The lists work exactly
| the same way - they discard ratings entirely and only take into
| account the quantity of books. It would be as if you said that
| the top 40 is the best music because everyone listens to it.
|
| So you don't think I'm all talk, a while back I got so fed up
| with this that I wrote my own script to scrape goodreads and find
| the actual best books, not just the most popular, and I found a
| wealth of really good and unknown books, including two books that
| are now my favorite books of all time. It was a side project that
| took me an hour. Why goodreads can't do this is utterly beyond
| me.
|
| Aaaargh!!!
| xuhu wrote:
| How did you define the actual "best books" ? I usually pick a
| group (Goodreads users in country x), scrape the books of all
| its users, and sort them by frequency:
| https://github.com/harjoc/goodreads-group-books
| PaulStatezny wrote:
| Would you share the titles and authors of those two books?
| johnfn wrote:
| Infinite jest by David foster wallace and only forwards -
| forget the author name off the top of my head. Infinite jest
| is pretty popular these days. The other I have yet to hear
| anyone say they have read.
| tomstuart wrote:
| I've read _Only Forward_ by Michael Marshall Smith. It
| stuck in my mind the same way that _Vurt_ did. I still
| think about the man with no head sometimes, and the idea of
| a road being different when you're going the other way on
| it.
| taeric wrote:
| I'm confused. What you describe is really just another form of
| popularity contest, no? Unless you have a set of reviewers that
| you value over others. One might call them the critical
| reviewers. (No, I'm not trying to be subtle)
|
| So, what books did you find? Why not make a post on your
| method?
| johnfn wrote:
| Not exactly. Goodreads will value a million people giving a
| book 1 star higher than 20k giving it 5 stars. I just sorted
| by average score.
|
| I posted the books in this thread (sorry, on mobile right
| now).
| taeric wrote:
| But that is still a popularity contest, of sorts. In
| general, any ranking system is a popularity system. Which
| is logical, as there is no objective ranking of books. That
| is, it isn't an ordered set.
|
| That said, I can see value in providing a score not just in
| the items, but on the ranking system used. Could even be
| adaptive based on genre. (Indeed, I would love a system to
| see if any books have factual errors and such. But, that is
| just trying to reinvent the citation systems of academia.)
|
| And understood on the mobile. Same boat for me.
| [deleted]
| moomin wrote:
| Everyone wants to fix Goodreads except Amazon.
| newbie578 wrote:
| The status quo regarding Goodreads and it's position in the
| industry is really interesting.
|
| There is not a single competent alternative to Goodreads, yet
| Goodreads just sucks! As simple as that, the UI is horrible, the
| UX is disgusting, the perfomance is that of toaster and still
| people are using it.
|
| I personally am using it for the last 5 years while continuously
| searching unsuccessfully for alternatives. If you think the
| website is bad, you should check out the Android app, never in my
| life have I seen a worse app by a popular company.
|
| I got so frustrated by Goodreads that on multiple occasions I
| thought of starting a competing product just to challenge the
| status quo, but as soon as I started dwelling deeper into it, I
| realized that there is just no real viable business model for it
| to be worth it.
|
| I guess that explains the current status of Goodreads and why
| there are so few competitors.
|
| How do you monetize a social network about reading books? I have
| spent way too much time thinking about it, yet failing to achieve
| a result.
|
| 1)You can't really sell books, since Amazon is already so well
| entrenched and honestly books aren't a really hot commodity.
|
| 2)Subscription for audiobooks? Again there is Audible, and Scribd
| is also doing a phenomenal business doing it, you pay $9 and
| listen to as many as you want audiobooks.
|
| 3)Affiliate marketing? Goodreads already does it, and it isn't
| really a business model with a good foundation.
|
| 4)Customized ads? This might be the "least" worst solution,
| although what could you advertise to people who read books? Their
| LTV (lifetime value of customers) isn't really high.
|
| 5)A paid social network? Good luck trying to grow a social
| network which asks it's users to pay $1 monthly.
|
| 6)The latest and craziest idea I had regarding it, was to make it
| a hybrid of Goodreads and LinkedIn. Where employers can see what
| types of books are their applicants reading. I.e. if I am looking
| to hire a backend intern, I am sooner going to hire the intern
| who read in his free time Effective Java, Clean Code, etc. since
| you can pretty much gain a good overall picture about a person by
| looking at the books he reads.
|
| I spent way too much time obsessing over this...
| dang wrote:
| The earlier related thread:
| https://news.ycombinator.com/item?id=24451428
| mekarpeles wrote:
| Howdy, Mek here -- I run https://openlibrary.org over at the non-
| profit Internet Archive (the folks that bring you the Wayback
| Machine).
|
| Open Library is an free, online California Library with millions
| of digital books to read and borrow. It's additionally an open
| catalog of millions of books which you may track like goodreads.
|
| Best part? If it's not to your liking, the whole project is open
| source! https://github.com/internetarchive/openlibrary
|
| Open Library has a very strong volunteer tribe of book-loving
| librarians, developers, and designers working to make the project
| better for our community.
|
| We meet once a week at 11:30am PT. Ask me for the link:
| mek+ol@archive.org
|
| RIGOROUS BOOK RECOMMENDATIONS: We're also cultivating a 2nd non-
| profit open source experiment called TheBestBookOn.com (it
| leverages Open Library's catalog) which allows book-lovers to ask
| for or make rigorous book recommendations:
|
| https://github.com/Open-Book-Genome-Project/TheBestBookOn.co...
|
| It's a very early prototype (we discuss development during our
| weekly Open Library call). It's being organized by Lauren
| Milliken, Aasif Khan, and myself and we'd love more contributors
| to join the discussion: mek+bbo@archive.org
| rexpop wrote:
| Fellow Goodreads refugees, you can import your lists into
| OpenLibrary.org.
|
| 1. Export: https://www.goodreads.com/review/import
|
| 2. Import: https://openlibrary.org/account/import
| olah_1 wrote:
| It seems like there is a strong desire to _not_ make
| OpenLibrary an alternative to Goodreads.
|
| See discussions here[1] and here[2].
|
| [1]: https://github.com/internetarchive/openlibrary/issues/3103
|
| [2]: https://github.com/internetarchive/openlibrary/issues/1964
| kirubakaran wrote:
| Thanks for your work mek!
| mekarpeles wrote:
| The philosophy behind thebestbook.com (which is currently just
| a looks-like demo -- you should help us implement it!) follows
| this essay on Less Wrong:
|
| https://www.lesswrong.com/posts/xg3hXCYQPJkwHyik2/the-best-t...
|
| Recommendations are better when you have enough info to draw a
| line rather than consider a single point.
|
| There are many websites online which give you detailed reviews.
| But how does their review compare to other similar books? And
| has this reader also read those books?
|
| Thebestbookon.com requires a reviewer to have read 3 books and
| justify choosing one of them as a winner (like a college
| basketball bracket).
| Jemaclus wrote:
| My problem with Goodreads isn't the recommendations engine. The
| recommendations are fine. I'm actually skeptical that any ML
| recommendation engine is going to recommend _better_ books than
| my friends will. The only thing I expect from a recommendation
| engine is _discovery_ , by which I mean finding new things that
| neither I nor my friends have read that look interesting. Whether
| they're good is another story altogether...
|
| My problem with Goodreads is actually the site performance. It's
| one of the most abysmally slow sites I've ever had the
| displeasure of using. Loading from page to page takes so long, I
| wonder if they're running on 486 machines in the background. It's
| unfathomable to me how something that has such a monopoly on the
| domain can have such terrible performance.
|
| It's so bad, that I often don't even bother going to Goodreads
| except when my TBR pile empties out, and then I spend as little
| time as I can (which is a long time because it's OH MY GOD SO
| SLOW) so I won't have to visit it again for a while.
|
| I wish it was open source, or something, so I could contribute to
| improve response times...
| BelleOfTheBall wrote:
| My most hated part of Goodreads is that if you type something
| in search and try to click the middle mouse button to open the
| resulting, highlighted book in the new window... it just copies
| the page you're already on. It's a site for discovering books,
| why do I have to open the landing page 5 times if I want to
| open 5 books? It's so counterintuitive to me.
| WrtCdEvrydy wrote:
| Discovery engines are pretty easy if you just use clustering
| unless you allow transitivity (book in two clusters can be used
| to suggest a book in either cluster)
| watwut wrote:
| If it is so easy, why most of them sucks?
| Godel_unicode wrote:
| Because it's only actually easy of you remove the
| irremovable thing that makes it hard. This is one of those
| tropes that honestly really hurts the credibility of ML in
| the eyes of non-practitioners. Practitioners get really
| excited about some 75% solution, and talk about how this
| thing which is bad everywhere is really easy. The average
| listener doesn't realize how hard that last 25% (why would
| they? They were just told it's easy!) and end up writing
| off the whole thing as snake oil.
| WrtCdEvrydy wrote:
| To be honest, 90% of the code takes 90% of the time and
| the remaining 10% takes an extra 90% of the time.
| WrtCdEvrydy wrote:
| That's the point... if you allow transtivity, you get
| discovery but your recommendations start sucking.
| watwut wrote:
| But my recommemdations sucks pretty much everywhere.
| simias wrote:
| Spotify pretty reliably finds me one or two interesting
| tracks in my discover weekly. That still leaves dozens of
| tracks I don't particularly care for (although I
| generally don't actively dislike them) but I still think
| it's a decent result.
|
| I guess the obvious problem is that for books the
| equation is different. If you get recommended 20 books
| and after reading them you only ended up really liking 3
| of them, then you'll feel like you've wasted a lot of
| time reading books you don't care for. Meanwhile if you
| listen to 20 audio tracks in the worst case scenario
| you'll have wasted an hour, and you can do that in the
| background while you do something else.
| asdfasgasdgasdg wrote:
| I'm glad the recommendations work for you, but I agree with the
| blog post author and echo their experience. I think Goodreads
| recommendations are awful. All of the other recommendation
| engines I use regularly (Facebook, Twitter, Amazon shopping,
| Amazon Prime, Google, targeted web ads, Netflix, Steam) work
| significantly better than Goodreads does.
| kobe_bryant wrote:
| god yes, I just google author name or book goodreads to avoid
| using their search
| monksy wrote:
| Honestly, I feel that most tech goes this way when you have a
| monoply. Everything has a nature lifecycle, theres new life,
| interest, peak, and death/replacement. However, with some of
| these large corps (i.e. Amazon in this case), they can choose to
| hamper the growth and avoid competition.
|
| A lot of our tech can/should be a lot better than what it is. Use
| the tech to help people collaborate/get together/share. That was
| the great thing about reddit in it's hayday.
| ericmcer wrote:
| One interesting facet of all these recommendation and ratings
| systems online (Yelp, Goodreads, Rotten Tomatoes, etc.) is that
| they don't provide a key value that in person recommendations do.
|
| When a person recommends a restaurant they are attaching blame
| for the restaurants performance to themselves. Its performance is
| a reflection on them and their credibility. It is very hard to
| replicate this on the internet, a place where people can suggest
| things with very little responsibility.
|
| If I strongly suggest a movie to someone and the movie sucks, I
| can be blamed for that. I don't know how to replicate that
| comfortable eschewing of responsibility that in person
| recommendations provide.
| cpsempek wrote:
| I'm skeptical of this person's ability to "know" what they don't
| want to read. E.g., they are recommended Shoe Dog and a King
| novel, which they claim they don't want to read. However, if
| other people have read similar books and rated them similarly to
| this person _and_ have read Shoe Dog and that King novel and
| rated those well, then this person may like those books. It seems
| they are assuming they won 't like them, but not for particularly
| strong reasons. One of my favorite authors is Haruki Murakami and
| I would have rated Colorless Tsukuru a 2 or 3. If that were the
| only Murakami novel I had read and I made the same assumptions
| this person made, I would have missed out on some of my favorite
| books.
| lazyasciiart wrote:
| Huh, I get recommended Murakami a lot but really didn't enjoy
| Colorless - maybe I'll try a different one.
| pilsetnieks wrote:
| Try something pre-2010. The 2010s aren't really
| representative of his other work nor, to be honest, quite as
| good as his earlier books.
| cpsempek wrote:
| If you are looking for more of magical realism Murakami has
| become known for, I highly recommend Hard-Boiled Wonderland,
| The Wind-Up Bird Chronicle. But really anything 1Q84 and
| earlier is good IMO.
| manigandham wrote:
| I don't create about recommendations as much. I get those from
| other sources and already have enough of a backlist to last a
| life time.
|
| Goodreads for me is for storing my history and ratings. Same with
| IMDB for movies. Both sites are terrible (and owned by Amazon),
| but I don't see much value in clones that don't do anything
| completely new.
| jacobobryant wrote:
| > Why would they recommend this book?
|
| If they're using collaborative filtering, there probably isn't a
| simple explanation. Basically, you feed in a list of "<user id>,
| <book id>, <rating>" and the algorithm generates a feature vector
| for each book and each user. So the reason some book gets
| recommended is because... the dot product of that book's vector
| with your vector was high. You can do this easily with off-the-
| shelf libraries, like Surprise[1] (I'm using that lib in my
| startup[2]).
|
| At least this is what happens in matrix factorization methods.
| Recommendations from k-nearest neighbor methods can be explained
| more easily, but knn doesn't scale as well.
|
| This is a minor drawback of matrix factorization--people have
| been shown to trust recommendations more if they understand how
| the recommendations were generated. Twitter recently published a
| super interesting paper[3] about how they generate
| recommendations at scale, and as a bonus their method is
| explainable. They create a model that describes the communities
| in Twitter--groups of people who follow the same set of
| influencers. Users and items are represented by vectors, where
| each element of a vector describes to what degree a user/item
| fits in a certain community. When generating recommendations, you
| can get the user's top communities and then fetch items for those
| communities. If you generated a text description for each
| community, you could include that with each recommendation.
|
| [1] https://github.com/NicolasHug/Surprise
|
| [2] https://findka.com/
|
| [3] https://www.kdd.org/kdd2020/accepted-
| papers/view/simclusters...
| rexpop wrote:
| Is this a good thread under which to have a more general
| discussion about data ownership and access? Goodreads is a
| Schelling point for book reviews, reading lists, and personal
| catalogs, but the API leaves something to be desired, not to
| mention the UI. Why shouldn't the Goodreads database be
| accessible to other applications? Why shouldn't the data be
| stored locally, or on our "own cloud"?
|
| Why can't we fix what's wrong with it? It's maddening that sites'
| UI is locked down, unfixable.
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(page generated 2020-09-12 23:00 UTC)