About these charts

This documentation is a work-in-progress, so apologies for incompleteness, incoherence, errors, omissions, etc...

Introduction

First off, I want to make it absolutely clear that there's no agenda here about how awards should reflect popularity, or that awards that don't meet someone's personal perception of what is "popular" are bad/fixed/etc, or any similar nonsense. (Although I am more than happy to point out cases where certain individuals or groups claimed to represent popular opinion, but whose idea of which books are popular don't seem to be backed up by the statistics.)

Anyway, these charts are an attempt to get an impression of what SF&F books - by which I broadly mean novels, see below for more details - might be the most widely read amongst (present-day) book readers, and which "classics" of the past have maintained their mindshare into the modern day. Books which have been nominated for awards are the sample set being used here.

Now, I definitely don't think any awards are flawless, but taken as a whole they do give an interesting perspective on the history of the field. Perhaps in some cases they are no more an indicator of quality than pop charts or box office figures, but both of those have led to interesting cultural analyses.

Nevertheless, a selection of the finalists for some of the highest profile and/or longest running awards seems a reasonable set of books to use. Another option might be the books that have been reviewed by long running magazines such as Locus or the BSFA's Vector, both of which have their reviews indexed by ISFDB - for example, recent issues here and here. Whilst I may well look at charts based on those books in the future, for now, award finalists seem to be a reasonable starting point.

I've had the idea to build something like these charts for a while, specific inspirations include the following:

Blog posts on File 770, specifically this and this, and similar posts by Nicholas Whyte.
Forum discussions about obscure novels, such as this thread on Reddit's /r/printSF, which raise the question of how you determine what works are obscure (or popular).
An episode of the Coode Street Podcast (no idea which one) where the hosts mentioned in passing that - and I'm paraphrasing from memory here - there was no way to know whether older books were still being read; at the time I thought to myself, "Goodreads surely?", but I don't know that the site UI makes it easy to get a macro-level view of many works at a time. (Plus, every time they refer to a book as "a major work", and I ponder to myself whether I should be embarrassed that I've never heard of it ;-). Update Episode 351 was released a few days before the first public release of these charts - although I didn't get to listen to it until a few weeks later - and has a brief discussion of what they most read SF&F novels might be (approximately 39 minutes in).

Background

ISFDB

The Internet Speculative Fiction Database is a - IMHO massively underrecognized - website with lots of data about SF&F authors and their books/stories. Data on the site is contributed by users, but - unlike Wikipedia or Goodreads - all changes have to go through a moderation step where an administrator of the site approves or rejects the change. My experience in building these charts based on data from both ISFDB and Goodreads - and prior experience using Wikipedia data - is that ISFDB is more reliable than others. (NB: I have contributed data to all three of these sites, so I don't have a particular dog in this fight.)

Goodreads

Have a look at the Wikipedia page if you're unfamiliar with this website/app.

Science fiction and fantasy awards

There are many - some will say, too many - awards for written science fiction, fantasy and horror. Rather than attempt to describe them all, please refer to:

The award directory on ISFDB
The Science Fiction Awards Database (SFADB)
The Wikipedia category pages for science fiction awards, fantasy awards, horror fiction awards and speculative fiction awards.

Concepts and Terminology

This section is here in part because some of the terminology comes from the Goodreads site, yet Goodreads itself is sometimes inconsistent or vague about the meaning of terms it uses. The below are the interpretations used for processing the data to generate these charts.

Nominees/finalists/shortlists

The term "finalists" is used throughout these charts, but depending on the award in question, "nominees" or "shortlist/shortlisted works" may be the more specific term in use. Most (all?) awards have a stage prior to declaring the winner where between 3 and 10 works are declared as finalists, nominees or the shortlist, and these are what are displayed in these charts.

The hope is that this small set of finalists provides a more useful view on the notable books of the year than merely focussing on the winner.

Ratings

Rating a book is when a Goodreads user gives it a quality rating from one to five stars. This is different from reviewing a book, which is posting a text review - there are unsurprisingly far more ratings than reviews, given the levels of effort involved.

In the context of these charts, we have no interest whatsoever in the rating values, whether individual or aggregated as an average. Rather, it is the number of times a work has been rated that is being measured. This is presumed to be a reasonable, if imperfect, proxy for the number of Goodreads who have read a book. Reasons why this might be an imperfect metric include:

~~Idiots~~ Some people rate books they haven't read. An extreme case as of May 2019 are the 1318 ratings for a book which was recently indicated may not even have been started to be written (as opposed to plotted).
Conversely, people may not rate books which they have read. One variant on this if the reader did not finish (DNF) the book - depending on how far into the book they got, and/or the reason for abandoning it, they may consider it reasonable or not to give the book a rating.
Some of the issues mentioned in the meaningfulness section further down this page.

Theoretically a better metric for measuring readership is when a Goodreads user "shelves" the book as "Read", as opposed to the other states of "To Read"/"To Be Read" or "Currently Reading". There are two issues with this:

I don't know if this data is available through the Goodreads API, it's certainly not included it the response to the API call being used here.
For some reason, when adding a book to your collection via the Goodreads website, the default shelf it is added to is "Read". At least in my personal experience of using the site, a better default would be "To Read", and there are many times I've only realized long after the fact that I'd accidentally added a new book to my collection with an incorrect shelving of "Read".

Publications and editions

"Publications" (aka pubs) is a term used in ISFDB, whereas Goodreads uses "editions". These can be broadly treated the same, although I think there are differences.

Any given book (aka work aka title) will likely be available in multiple publications aka editions. These could be the type of media e.g. paperback vs hardback vs ebook vs audiobook, but also translations into other languages, reprints (possibly with new covers, or introductions, etc).

ISFDB records multiple - ideally all - publications of a work, and the code that generates the charts needs to pick one that has an ISBN to query the Goodreads API for the ratings count. We could get incorrect/misleading data back from that API if one of the following happens:

The ISBN we picked is for an edition which hasn't been "combined" with the others in Goodreads, resulting in a ratings count much lower than it should be. This is easy enough to fix in Goodreads (if you have the "librarian" privilege); the main issue is spotting it happening.
The ISBN picked is for an omnibus edition, which will almost alaways have a lower ratings count than the standalone edition. If this happens, then it's probably a bug in my code, although I've tried to catch all the cases where this happens/happened. Again, this is usually easy to spot, but as ISFDB records box sets as omnibuses, there are a few cases that don't stand out as obviously as orphaned editions.
There's a higher-than-expected number of cases of the same ISBN being used on two unrelated books, for example this. These can obviously cause the wrong ratings count to be returned from Goodreads.

Methodology

Overview

All the data about awards, categories, winners and finalists/nominees/ shortlists comes from ISFDB, specifically the database dumps they kindly make available each week.

From the database, ISBNs for editions of the award winning/nominated works are obtained. (This isn't quite as trivial as it might seem, see the details section below.) The ISBNs are then used in a query to the Goodreads API to get the counts of the number of people who rated the book.

All the collected data is then used to build SVG charts, with JavaScript used to provide some basic interactivity. Some basic HTML web-pages are also created.

Implementation

A local MariaDB instance runs the ISFDB database, and is queried by Python scripts for award data. These scripts also query the Goodreads API for the stats, which are incorporated into the data in memory. The scripts output SVG and HTML in a fairly crude way, and the resultant files are copied to a public webserver.

The scripts are initiated manually, but then run without intervention, taking around a minute if all Goodreads API is in a local cache. There are a few configuration files to bodge over inconsistencies or weirdnesses in the data e.g. books which have ISBNs in Goodreads that aren't known to ISFDB, nominees that aren't books (e.g. Wheel of Time in the 2014 Hugos).

All the SVG charts are complete in themselves (i.e. no external resources such as JavaScript or CSS files) and so can be saved and used in other applications that support SVG, albeit without interactive functionality in applications (e.g. Inkscape) that don't support the required technologies.

Details

Notable pain-points whilst developing and testing included:

Trying to pick the best edition of a book from the ISFDB database, in particular avoiding omnibuses, as these invariably have lower numbers of ratings than "proper" editions.
Trying to spot if a "bad" edition has been returned in the Goodreads API data, by which I mean one which hasn't been "combined" with the other editions of that book, and consequently has a far lower ratings count than they should. (This is an area where you can see the benefit of ISFDB having extra verification and modaration steps for user changes.)
Fighting XML pedantry about error-less markup, properly encoded Unicode entities, etc - the latter is still unfixed, which is why some of the international charts look pretty horrible.

Pre-emptively answered questions

Why aren't novellas/short fiction/the Tiptrees/some other award not covered?

First off, the code that generates these charts is utterly dependent on the data for awards being in ISFDB, so if the award you'd like to see isn't there, it won't be here.

Short fiction - by which I mean the individual novelettes, short stories, flash fiction etc, rather than the publications which might contain them - is probably a non-starter, primarily as they don't have individual ISBNs, which are necessary for the API queries to Goodreads. Even if we were able to map an individual story to a containing publication - which should be possible with the ISFDB database - we'd then need to determine which of potentially many publications that included the story (example) should be used to get a meaningful count? It's also worth noting that Goodreads has had an uncomfortable relationship with magazines.

Novellas might be easier to deal with, given that recent novella finalists have been available as standalone publications with ISBNs. However a glance at the Wikipedia page indicates until fairly recently most were in the pages of magazines, and thus we are back to the same problems as for shorter fiction. Perhaps this might be solvable with some manual overrides, but as I'm not a reader of shorter fiction, this isn't something I'm personally interested in looking at. Any volunteers?

(For what it's worth, I have included a chart for the Locus Best Anthology and Best Collection awards, although those fit more comfortably into the world of book-like things with ISBNs. EDIT: These two charts have been temporarily removed as the generation process was causing confusion for any novels that might have been included within a collection.)

I've avoided the Tiptree Award for the time being, because the data seems a bit messy: lots of the finalists are shorter fiction with the issues mentioned previously, or not even written fiction at all. Additionally there are several "meta records" in the ISFDB for it that I suspect shouldn't even be there. I'll probably come back and take another look at it at some point, but I'm not considering it a priority right now.

How meaningful are Goodreads ratings counts?

Quite possibly they are completely bogus and shouldn't be paid any attention - I'm not going to try to convince you otherwise if that's what you think. This comment by Camestros Felapton at File 770 (which I have shamelessly stolen without asking permission to reproduce here) is similar to my own feelings about this data versus potential alternatives:

"...it is more a case of any data source in a storm: there’s no really good source of data on what is being read that is readily available. Bestseller lists are gamed and rely to much on physical book stores, Amazon is opaque about its methods and publishers are secretive. Goodreads has issues (of which said Amazon is one) but it is dominated by people who read lots of books."

There are some published facts and prior research that may give a better idea about the usefulness of these stata though:

As of early June 2019, Goodreads claims 85 million members, a number also reported here. How many of these users are active is, as with most social media sites, unknown. For what it's worth, my own user account created in Summer 2016 has an ID in the 58-million range, which roughly - but not exactly - tallies with the historical chart in the Statista link, assuming that Goodreads user IDs are allocated sequentially.
The fantasy author Mark Lawrence has a number of posts analysing data gathered from a number of fantasy authors about how their sales correlate with the number of ratings on Goodreads. It doesn't look like he tags/categorizes his blog posts, so I might have missed some, but the ones I know about are:
There is related commentary by Kameron Hurley, and a couple of /r/Fantasy threads here and here
There are other 2015 studies of Goodreads statistics, by Jared Shurin/Pornokitsch here and by Chaos Horizon here here.

(If anyone knows of any other relevant studies or posts, I'd love to hear about them!)

It's also worth noting that Goodreads stats aren't immune from being gamed - for example, look at this very very curious ratings spike about which one can only ponder the motivation... (Here's a screengrab in case you're reading this after the data is no longer visible on Goodreads.)

Can I get the raw data?

Short answer: No(t yet).

Pedantic, unhelpful answer: Yes, the ISFDB downloads are here, and the documentation for the Goodreads API is here, so go and knock yourself out!

Proper answer: there are Terms of Service associated with the Goodreads API that make me leery of giving out the raw data - I'm looking specifically at items 2, 3 and 6 on that page. Of course, putting these charts online is arguably "redistribution", but hopefully this use is considered reasonable, especially when you consider that similar data - presumably manually gathered - has previously been published online - see links near the top of this page. I do intend to make the code that generates these charts available though - most (possibly even all) of the code to get the data out of ISFDB is on GitHub, and I'll upload the code to query Goodreads and output the charts up once I've tidied it up sufficient that I think it's fit for human consumption.