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I don't see any details about its algorithm, just that they use a recommendation engine? Things like this aren't proprietary info, they're just how recommendati
by ChefboyOG 6y ago
I don't see any details about its algorithm, just that they use a recommendation engine? Things like this aren't proprietary info, they're just how recommendation engines work:
"Once TikTok collects enough data about the user, the app is able to map a user's preferences in relation to similar users and group them into "clusters." Simultaneously, it also groups videos into "clusters" based on similar themes, like "basketball" or "bunnies.""
Although I do wonder, and maybe someone else with more experience could shed some light here, whether or not it is likely that TikTok has some fundamentally super advanced algorithm, or if they just do a better job of collecting data/training & evaluating their models?
- xnx 6y agoMore data beats smarter algorithms any day, and TikTok gets a lot of data because its videos are so short and interaction rate so high. There are tons of signals it can use as inputs: How much of a video did you let play before swiping next? How many times did you let the video loop? Did you like? Did you comment? Did you like a comment? Did you click through to the profile? Did you view other videos from the profile?
- judge2020 6y ago> Did you click through to the profile? Did you view other videos from the profile? Probably why multi-part videos are so popular (you have to click their profile then find the part 2 video to finish the story they were telling).
- ComodoHacker 6y agoSounds like a way to game the system.
- ChefboyOG 6y agoI never thought of it like this. Just had one of those mind exploding moments as I realized the frequency of interactions on TikTok vs other platforms and the virtuous cycle it creates (order of magnitude more data -> better recommendations -> even more interactions). Thanks for this.
- xnx 6y agoGlad I was able to help introduce you to that idea. I was first introduced to it by Peter Norvig (Google): https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/35179.pdf https://static.googleusercontent.com/media/research.google.c...
- ramraj07 6y agoI don't buy this argument. YouTube ostensibly has a metric ton of information like this and even if tiktok has more training data now, I'm fairly sure their training data in principle was smaller than what YouTube historically had given their decades long presence and their ubiquity in the internet. This is on top of the documented effort by YouTube to perfect their recommendation algorithm using the best ML minds they got [1] only to polarizing response from its users. Clearly tiktok has other advantages (homogeneity in some content characteristics, viz. Extremely short videos which probably correlates to their simplicity) and has clearly tuned a fundamentally better recommendation algorithm that even the minds at Google brain couldn't figure out. [1] https://www.theverge.com/2017/8/30/16222850/youtube-google-brain-algorithm-video-recommendation-personalized-feed https://www.theverge.com/2017/8/30/16222850/youtube-google-b...
- robjan 6y agoYouTube has the problem that all Google products have: they put you in a filter bubble which you can never get out of. The algorithm also optimises for more "long form" content and it's pretty well known that the optimum video length is around 10 mins.
- deleted 6y ago[deleted]
- jassany 6y agoif you simply erase you watch history that will reset your recommendations, always works.
- Drew_ 6y agoYouTube's recommendations are arguably just as good as TikTok's in my opinion. The only difference is that YouTube places the burden of choice on you while TikTok makes every choice for you. If you don't quickly find something you'd like to watch on YouTube you're very likely to leave and find something else to entertain you. Meanwhile TikTok is automatically feeding you an infinite source of quick and easy to digest content, all of which you'll probably like to some degree. YouTube could do something similar and give users an automatic continuous feed (ala a TV channel), but I think YouTube's content is much too longform to work well in this format. This burden of choice problem affects Netflix in the same way which also has superb recommendations.
- basch 6y agoThis article was popular here when it was published. https://www.eugenewei.com/blog/2020/8/3/tiktok-and-the-sorting-hat https://www.eugenewei.com/blog/2020/8/3/tiktok-and-the-sorti...
- gcmac 6y agoI’d say it’s more likely they have super advanced/clever ways of doing the latter. The algorithm could be a simple dot product and the result could be great or terrible depending on how good the feature extraction is. Pulling useful features out of videos is no small task. The fact that everyone raves about how good the recommendations are indicates to me that this is where their innovation lies.
- xnx 6y agoThere's so much good meta-data (likes, comments, duration, sound used, views, like/view ratio, skips, loops, subscribes, etc.) that I'd be surprised if they were digging into the contents of the video at all right now.
- jakear 6y agoThey could also be digging only into audio, doing speech recognition on it, then clustering the text. Augment that with the text users have put into the video directly using the in-app editor and you have some pretty solid data.
- ramimac 6y agoIf that were true, it'd be interesting to see if they push out support for close-captioning. It's an accessibility push, but also would leverage a lot of the same capabilities...
- novok 6y agoI would also start doing image recognition in the video frames, to extract things like gender, objects, etc.
- thekyle 6y agoWould this have any advantage over just using video embeddings (or a sequence of frame embeddings?) which in theory should capture those things in vectorized form.
- disgruntledphd2 6y agoThey always get a response to every video that you start watching, making their training data much, much better than that of Facebook or Instagram.