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Tweets to Citations: The Impact of Social Media Influencers on AI Research
- lordswork 3y agoAs much as I dislike all the baggage that comes with Elon owning Twitter, it is the only place I know with a critical mass of AI talent sharing papers and thoughts. Even in read-only mode, it's incredibly useful as a way to stay up to date with interesting AI papers and discussions. Does a good alternative to this exist?
- ronsor 3y agoI wish someone would scrape and mirror Twitter-X (fully, not just proxy like Nitter). I know Musk would be upset though.
- 3abiton 3y agoI struggle to keep up with the current trends in AI, do you have any twitter community recommendations to follow?
- carlossouza 3y agoThe growing pace of new papers, especially in CS, is a hard problem to solve. We created this tool to help: https://trendingpapers.com/ https://trendingpapers.com/ The website was launched in October. It is already used by researchers in most of the leading universities and tech companies and is growing fast. Let me know what you think.. cheers!
- obblekk 3y agoThis is super cool. I've often wondered why google scholar didn't use pagerank over the citations... and now you've done it! Props!
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- dr_kiszonka 3y agoVery cool! Would it be possible to order category filters alphabetically?
- carlossouza 3y agoYes, totally! That's a great input, thanks!
- pfd1986 3y agoNice. Is this open source and/or are you looking for help in any way?
- carlossouza 3y agoThanks! That's something we are considering, given how many people mentioned it and offered help. Right now, the help we need is writing a paper detailing all aspects of the system and comparing it with similar systems. We have a group in Slack: if you want to contribute, that would be great!
- lukasga 3y agoLove the site, but the one thing I am missing is instantly seeing what papers are trending right now, instead of having to manually select a timeframe. Think hacker news frontpage. Would be interesting to add a "hot" filter, or similar. Average weighting by exponential decay over time? Not sure how you usually do that with pagerank.
- carlossouza 3y agoThanks! Yes, that's in the roadmap; I believe it will be complete in 3-4 cycles. Right now, we are finishing the topics module. It will provide us with more granular filtering tools, and enable us to also discover trending topics, etc. It will be eye-opening... but it's taking longer than expected because of the dataset size.
- penjelly 3y agohave you got a public API? id love to add this data to a free app i put together.
- carlossouza 3y agoNot yet... great idea, thanks! We’ll add to the roadmap
- brucethemoose2 3y agoIn certain topics, Discords and Github repos. ...Yes, basically siloed off and unsearchable.
- DaiPlusPlus 3y agoDiscord is where our conversations go to die, yes; but (non-private) Github repos are clonable and very searchable - so I'm not sure why you wrote that.
- downWidOutaFite 3y agoIt's why big tech killed rss, they want to own our peer to peer channels.
- bugglebeetle 3y agoYeah, various AI Discords, like the Nous Research server.
- daxfohl 3y agoBack in the day, Google Reader was great for this. It's still hard to fathom that nothing ever replaced it.
- jerpint 3y agoHuggingface is slowly trying to get their own user base to adopt paper conversations
- nomilk 3y agoAny recommended accounts to follow; is there a "@Rainmaker1973" for AI papers?
- GaggiX 3y agoI use https://huggingface.co/papers https://huggingface.co/papers and frankly more than enough, usually anything significant enough has a paper there or is mentioned in the papers unless it's completely proprietary stuff (Midjourney, NovelAI etc) so they're not very interesting from a research point of view.
- jimmySixDOF 3y agoThere is a weekly paper reading group around the Latent Space podcast folks
- devindotcom 3y agoDon't underestimate the power of informal networks. Buzz is hard to quantify but it clearly has a huge effect on "real" metrics like citations.
- paulpauper 3y ago"Computer Science > Digital Libraries" how does this even merit inclusion on arxiv? Does it even count as science? We're talking meta-computer-science. Meanwhile, It's hard enough for me to get the endorsement to publish my actual math paper on there, which has afik new results. The computer science section of arxiv feels like a giant citation ring of mediocre, math-light papers.
- Ar-Curunir 3y agoComputer science is not mathematics. There's plenty of empirical work to be done in CS, including HCI.
- paulpauper 3y agoI may as well publish under a CS category if that is what it takes.
- dopylitty 3y agoIt’s basically academia washing for the new tech bubble. They saw how closely and uncritically people followed papers about COVID and realized if they released “papers” about whatever llm product they were working on it would lend some kind of credibility that they never got with cryptocurrency or Web 3.0 or the metaverse.
- actualwitch 3y agoCrypto tried the academia angle, every shitcoin had a whitepaper similar to llm ones.
- ansk 3y agoSo glad the AK account exists. As a researcher, I've always wanted some guy with an econ degree and a year of ML eng to recommend me papers after glancing at them for maybe 30 seconds. I am genuinely baffled that researchers in the field think there is any value in the service AK provides. I'd wager I could create an equally effective bot with the following process: 1) Create a historical dataset of publications and their citation counts 2) For each publication extract the following features: - H-index of first author - Maximum H-index of all authors - Number of author affiliations in {top-10 school, deepmind, meta, openai, nvidia} - Number of times the phrase "state-of-the-art" appears - Which latex template is used (NeurIPS, ICML, etc.) - Number of images in the paper - Whether there is an image on the first page - Whether "all you need" appears in the title - Whether the publication has a linked project page 3) Train a shallow decision tree with citation counts as the regression target
- Imnimo 3y ago"Do I recognize the latex template" is my number one filter when clicking through the new arxiv papers each day, so I definitely buy that that would work.
- icyfox 3y agoA friend of mine created a bot to do basically this, except it also looks at the current page rank associated with researchers recommending that paper. I've seen a lot of good looking papers (decent school/group/conference submission/etc.) that don't end up contributing to the field. Top researchers and Professors tend to have a better intuition of importance by reading the abstract and a quick skim.
- jfi8 3y ago[dead]
- abidlabs 3y agoThere are have been many, many services that have tried to automate paper selection based on these heuristics. None of them have had the staying power of AK's account. As someone with a PhD in machine learning from Stanford, I can attest AK's taste is quite good.
- jph00 3y agoDespite the paper's claims to the contrary, they most likely have the causality absolutely backward. The two accounts they analyse, AK (@_akhaliq) and Aran Komatsuzaki (@arankomatsuzaki), have much better taste than anyone or anything else I've come across that are as prolific as they are. There's a reason lots of us ML/AI researchers follow them closely, which is that over an extended period of time we've noticed that they keep surfacing interesting and important work. They do a much better job of it than some random reviewer, so you would not expect some other papers with the same review scores, venues, and embeddings to have the same citation counts. But this is the premise that this paper entirely relies on as the basis of the analysis, and as a result the paper fails to make a strong case. The idea that thousands of researchers would decide to follow two particular Twitter accounts for no good reason, and would like and retweet posts from those accounts just because they're "influencers", makes no sense at all. Accounts become influencers for a reason. In this case, the accounts are not from people who are otherwise famous for some external reason -- literally the only thing they're known for is posting papers. If they weren't good at finding papers that researchers found interesting, they wouldn't get followed. BTW, some years ago, Miles Brundage's Twitter account was the main one that researchers followed for this purpose. Nowadays he's the head of policy at OpenAI and no longer does this. But back when he did, the '@brundagebot' bot was created that tried to replicate his curation choices using an algorithm.
- nsagent 3y agoI posted a related paper a couple of days ago [1] titled "Promotion of Scientific Publications on ArXiv and X Is on the Rise and Impacts Citations" [1]: https://news.ycombinator.com/item?id=39124309 https://news.ycombinator.com/item?id=39124309