出版与作家生涯2020newstatesman.com
Goodreads 对图书讨论领域的统治可能即将结束
Goodreads’ reign over the world of book talk might be coming to an end
导读
这篇报道讨论 Goodreads 长期停滞、作者和读者开始寻找替代品，并把 Amazon 的垄断视为问题根源。评论区提供了对平台、算法推荐和不同读者群体的第一手观察，值得写作者一读：它提醒我们，推荐机制、平台激励与读者分层如何共同决定一本书能否被看见、被讨论。
可以直接用的写作要点
- 01
把平台的“停滞”当成写作素材：追问背后的商业动机，比单纯抱怨产品难用更有说服力。
- 02
写书评或推荐时先想清楚受众：是“书荒”的泛读者，还是待读清单已经排到几年后的重度读者，两者需要完全不同的写法。
- 03
论证要落到可复现的具体例子上（比如搜索“holiday heart”找不到、加上作者名就能找到），一个细节胜过一段抽象断言。
- 04
别把算法推荐当成万能解法：个性化推荐投入巨大尚且效果平平，写作与选书最终仍依赖人的判断和策展。
HN 评论精选
Goodreads 核心价值是“书单和社交”，搜索与推荐长期失效，但用户宁可要简陋可用的工具，也不要大公司式的过度改造。
我从 Goodreads 上线不久就开始用，它大概是我用过最烂的网站；但我宁愿它这样“良性 neglect”，也不想要亚马逊主站那种“改进”。我只把它当成已读和在读的书单，顺便看看朋友在读什么。它的搜索烂得可笑，似乎比拿正则去匹配一串书名还差，但我最后总能找到。推荐也很糟：我标记并评分过上千本书，它从没推荐过一本我觉得有意思、后来真去读的书。我喜欢它现在的样子——古旧但能用，像一座图书馆。
prepend查看英文原文
I have used goodreads since soon after launch. It’s probably the worst site that I use, but I prefer it’s benign neglect over the “improvements” made on the main amazon site. I just use it as a list of books of I’ve read and am reading, and to see books that my friends are reading or have read. It’s been funny to me that the search is horrible and seems to be something worse than just regexing a list of book titles. But I eventually find what I’m looking for. It’s sucked as long as I can remember. The recommendations are also really bad, it has never recommended a book to me that I thought was interesting or I ended up reading. This is despite having over a thousand read and rated books from me. I’ve been waiting for them to be able to search all the books I don’t know and find one that I will like. I kind of like the site as it is quaint, but functional. It’s like a library in that way.
垄断导致产品停滞：当推荐服务于平台利润而非读者利益时，推荐引擎就失去可信度。
“它停滞了：亚马逊把对新书讨论的有效垄断握在手里”——这是全文的关键。这和 Oracle 收购 MySQL 一样：曾经有前途的技术如今停滞不前。Goodreads 本可以帮助读者找到更好的书，但亚马逊喜欢现状——它推荐的是对自己生意有利的书，而不是对读者最好的书。十年前亚马逊推荐什么书我都买；现在我不用了，因为它只推利润率高或符合亚马逊战略的书，它作为推荐引擎已不可信。
Hokusai查看英文原文
> Instead, it has stagnated: Amazon holds on to an effective monopoly on the discussion of new books This is the main point. It is the same thing that Oracle purchasing MySQL. What once was a promising raising technology is nowadays stagnant. (Interest over time https://trends.google.com/trends/explore?date=all&geo=US&q=%2Fm%2F05ynw,mysql) GoodReads could help to find better books to read. But, Amazon likes the current state where Amazon recommends the books that are good for their business and not the best for the reader. 10 years ago, I would buy anything Amazon recommended on books. Nowadays, I do not use Amazon anymore as it just promotes books that, I guess, have larger profit margins or align better with Amazon strategy. It cannot be trusted as a recommendation engine.
读者是分层的：重度非虚构读者不需要推荐功能，新平台若只服务泛读者就会失去读书文化的骨干人群。
文章很快从批评 Goodreads 转向吹捧 StoryGraph，但 StoryGraph 那些新功能似乎只面向一部分用户：读小说或最通俗科普类非虚构、并且想要新书推荐的人。我所在的 Goodreads 亚文化完全不同：我们的待读清单早已超出有生之年能读完的量，根本不需要自动推荐；我们写大量严肃非虚构的书评，不只看大众畅销书；“dark”“edgy”这类标签对我们没意义，能加“触发警告”也是抓错了重点。我们大概是少数，但是很有存在感、被认可的少数——比如独立书店就靠我们这类人活着，任何想维持读书文化的新网站都该把我们考虑进去。
Mediterraneo10查看英文原文
The linked article soon goes from criticizing Goodreads to hyping The StoryGraph as a Goodreads competitor. However, all the great new features of The StoryGraph seem targeted towards only one portion of the Goodreads membership: people reading fiction or the most pop-sci-type nonfiction and who want recommendations for new stuff to read. My own bookish, nerdy Goodreads subculture is very different: we already have more books on our to-read list than we could realistically get through, we don’t really need auto-generated recommendations for more. We review a lot of serious non-fiction, not just the mass-market stuff, and genre tags like "dark" or "edgy" don't seem relevant, while being able to add "trigger warnings" misses the point. Yes, GR users like myself are probably a minority, but we’re a very established and recognized minority. We're the sort that keeps some independent booksellers alive, for example, so any new site that aims to maintain a culture of books and reading ought to take us into account.
搜索问题一半是用法问题；同时别低估算法推荐的成本与难度，它未必是读者真正需要的东西。
作者抱怨在 Goodreads 上“根本找不到书”，其实任何查询只要加上作者名就一定能找到你要的书，别只搜书名——这该是常识（在书店你也不会只跟店员说“你们有《Holiday Heart》吗”，而会报作者名），但显然不是人人如此。作者说搜“holiday heart”找不到 Margarita García Robayo 那本书的前几项，可搜“holiday heart robayo”就能找到。至于文章其余部分：认为靠一个人业余时间、预算拮据的初创公司就能轻松做好算法推荐，实在不可信。Netflix 花了数千万甚至上亿美元、拥有全球最好的工程团队之一，人们照样抱怨它的推荐。为什么大家会觉得算法推荐很容易，甚至很可取？
freddie_mercury查看英文原文
The author complains that it is "impossible" to find books on Goodreads. Simply adding the author's name to any query will always take you to the book you are looking for. Don't just rely on a title. Which should be common sense (if you were at a bookstore you would always tell the clerk the author's name and not just say "Do you have Holiday Heart?") but apparently isn't. The author complains that searching for 'holiday heart' didn't show Margarita García Robayo's book in the top hits. But searching for 'holiday heart robayo' does. As for the rest of the piece...the belief that algorithmic recommendations are going to be easy for some shoestring budget startup run by a single person in their spare time is somehow going to do a good job simply isn't credible. People still complain about Netflix recommendations and they've spent tens of millions of dollars, possibly over a hundred million dollars, on it and are one of the most valuable companies on the planet with one of the best engineering teams on the planet. Why do people think algorithmic recommendations are easy? Or even desirable?
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