Hacker News Reader

Comment by mhandley | Hacker News Reader

The research community really should do a better job of engaging with the wider world, irrespective of whether it increases citations. For example, I had this paper in Hotnets 2019, and about 80 people saw my presentation. But I also spent some time, turned it into a little video and put it on YouTube. 360,000 people have seen it there. Now the subtleties were probably lost on many of those people, but if only a few of those people got something out of it, then it will likely have had more impact than the original paper.

https://youtu.be/m05abdGSOxY

View on HN

I think the general trend of researchers becoming more media-savvy is great. But I also get the sense that researchers are increasingly choosing to work on Twitter-friendly topics (e.g., sensational, visually striking, reducible to sound bites) — whether that’s also positive I’m not so sure.

I wonder if there's an inverse relationship between the level of pressure on scientists to publish, tweet, blog and demonstrate the social relevance of their work, and groundbreaking advances in fundamental physics.

I don't think so. The culture of publish or perish is certainly detestable and I don't think 160 characters are enough for a synopsis. But I don't think it negatively affects research. At least I hope so.

Fundamental research and humanities both have these funding issues. It may be worth a discussion if these fields could benefit from increased public funding, because some forms of research don't result in an immediate economic benefit.

I'd be really surprised if it didn't have at least some negative impact, not so much because of the amount of funding but because of what you have to do these days to get the funding. The more time and energy you force academics to spend on journal/conference submissions, grant proposals, impact assessments, and public outreach, the less they have to spend on research. I'd expect it to be especially true for more abstract subjects as they're harder to distill into a concise form or to describe the social impact of, and often require protracted periods of intense study/thought which admin responsibilities distract from.

Add to that the number of distractions that everyone is subjected to in the modern world, and I start to feel like it's no wonder we're still struggling with quantum interpretations or going beyond the standard model.

Now, I'm not saying that we should reduce the number of conferences or papers, or amount of outreach. Just the amount of time academics need to spend on them. Of course there will always be a few of the elite who will find time to sit and think for hours per day outside of these, nevertheless the harder you make it the more knowledge will suffer.

There was an opinion piece on PNAS a few years ago that argued just that, no hard evidence though:

https://www.pnas.org/content/113/34/9384

Thanks, that was a good read. Perelman is actually one of the examples I had at the back of my mind.

This is pretty much guaranteed to happen as explained by “the medium is the message”: https://en.m.wikipedia.org/wiki/The_medium_is_the_message

This reminds me of a story from Steven Levitt.

He published Freakonomics together with Stephen Dubner then went back into academia while Dubner went down the podcaster route.

15 years later, Dubner has reached millions of people with his work and Levitt recently started a podcast and soft quit academia after realizing that one of his best papers after years of research and hard work got 3 citations. He assumes fewer than 20 people will ever read that work.

I'm not sure why number of views/reads is the metric to optimize for, though. I'm sure more people listen to the Joe Rogan Experience than have read a Mathematical Theory of Communication. Does that intrinsically make it worth more?

Depends on your goals. Do you want to have impact or chase obscure brain teasers?

Size of impact is orthogonal to quality of impact, people who chase social stats seem to forget this fact.

Who said anything about social stats?

Levitt in particular says he feels like his research can have a bigger impact if it’s shared broadly with people than if it reaches 10 other academics and that’s it. We’re not talking about likes on social media, we’re talking about breadth of audience for academic research and how scientists can do better than chasing meaningless citation stats.

Levitt talks about his thought process in this wonderful episode of Freakonomics. https://freakonomics.com/podcast/math-curriculum/

> Who said anything about social stats?

You did.

> Dubner went went down the podcaster route. 15 years later, Dubner has reached millions of people [...]

I assume this is measured in terms of subscribers or listen counts.

I'm not saying the Freakonomics Stevens have/haven't had quality contributions to the world, I'm not even saying anything w.r.t. average podcast quality vs. average academic paper quality. I'm only saying that people often measure impact along only one dimension.

I gotta say A Mathematical Theory of Communication is not an obscure brain teaser, and has had quite an impact.... so your reply doesn't really reflect what the previous poster was asking about...

Levitt is leaving academia? Wow - that’s news!

Might be more of a sabbatical.

This is the Freakonomics episode where he talked about this https://freakonomics.com/podcast/math-curriculum/

Interesting. I will listen. He’s a distinguished service professor which is as high as you can get.

This sounds like an empirical side project rather than leaving academia, no? Has it been long enough to see the results?

Interesting that they put their hopes on data fluency on the College Board while the SATs are falling out of fashion.

Most research is not useful or suitable to the wider world.

I guarantee a cottage industry of YouTubers would pop up digesting and rewrapping that content. Today, it's probably too inaccessible for them to do so.

I sincerely doubt it. There is much more that is published than the general public has an appetite for. Even in a narrow scope, people have a limited appetite for any particular form of content before they're satiated. If too much content is produced for any particular topic, people will burn out and tune out.

Two Minute Papers is a great example of this:

https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg

Two minute papers is fantastic! I just wish that all of the papers he covers had source code available. A few of them I've gotten excited about and hopped around the net to read the paper only to find no code available.

This is the state of science in a lot fields unfortunately. Many reviewers skim the paper, put in a thinly veiled complaint about why their own paper was not cited, and don't bother with the code.

The code itself is always usually a mess: no readme, no license, random binaries, and a 'pipeline' which is simply a bunch of perl and python scripts cobbler together from snippets found on the web.

People publish, then move onto the next project. There is no maintenance.

> This is the state of science in a lot fields unfortunately. Many reviewers skim the paper, put in a thinly veiled complaint about why their own paper was not cited, and don't bother with the code.

Excuse me. Is this your actual experience or the meme that everybody is simply repeating?

In the admittedly few papers I have published, the reviewers’ feedback has been a net positive I wouldn’t be without.

Also, the general focus on code in science here on HN is so incredibly myopic and narrow minded. Code for research are not high-profile software projects. They are a piece in the toolbox used to solve a problem. Some grow to become larger projects, some fulfill their purpose and stay fixed in time.

Actual experience. The state of code in Bioinformatics is a joke. Many do not know the word 'conda' or 'docker', and example datasets are far and few between.

In my case, I'm not a researcher or even a computer scientist (EE). I'm just a person with a curiosity in various topics. I find the language in papers to be a big barrier. Even cludgy bad code in ten different languages is more readable to me than the strange symbols and vague diagrams.

I agree with you that this is research and there's no reason for it to be pretty. The fact that it's unsightly and brittle makes a lot of people reticent about sharing it online since it could reflect on the quality of their non prototype code. Maintenance is a large burden and once the original goal of the paper has been proved, there's little benefit to the researcher to keep the code around, so I understand why they might say let's not release it at all.

A recent example of this was I was building a gesture classifier using an accelerometer to generate data. I decided do use an svm as based on what I had read, it would be the simplest to port to the microcontroller I was using. I was getting decent performance but needed to extract better features. I found several papers talking about the topic with some novel ideas and their impressive results. While it was nice to know that accuracy could get that high, none of the papers explained how the features they extracted were made. It was usually a one or two sentence line about using both time and frequency domain data.

Well, there are gradations to "the wider world". I don't know about you, but I read a lot of stuff that's way outside my area. That's why I hang out here. There's a huge gulf between "suitable for mainstream TV" and the opaque and overly compacted research paper. Places like New Scientist and Ars Technica fill this gap to some extent, but they tend to oversimplify to appeal to a wider audience. I'd rather hear it from the authors in an only slightly dumbed down form.

Even as an ambitious and educated outsider, the stuff you're looking at is almost certainly not representative of most research in those respective fields. When weighted by pages, most research is boring and truly only of interest to the few dozen of specialized researchers in that subfield.

Same feeling here. That's why a friend of mine and I created Abstra. We ask authors to come and do some vulgarization themselves. The summaries are structured exactly like most papers: background, findings, and methods. Quick and to the point. There is an incentive for both as the reader gets quality info from the source and the researcher gains audience and exposure. We're at the prototype stage Check it out abstra.co.uk, would love to have your feedback!

I spend a lot of time reading research papers in various fields that the original authors were not directing toward me as an imagined audience, and get plenty of value from papers that could be called “unsuitable to the wider world”.

The ability to use the web, citation indices, etc. to discover and read papers has made the whole of the scholarly literature much more useful to me than it would have been a few decades ago.

Would you say the wider world is interested in watching a video on "Using ground relays for low-latency communication in Starlink"?

If Tom Scott or a similar personality did a video on it, yes.

If you present your research such as even a 5-year-old kid understands it then it will be suitable for the wider world.

That video is brilliant, by the way. I just watched it all the way through — it makes sense that a video that had such a high learning bandwidth (For lack of a better term) gets so many views.

What's interesting is that I didn't make that video for a general audience. I made it for the networking research community, so I didn't bother to explain what Dijkstra's algorithm is, or any of the basics really. There are also a number of graphs which conventional wisdom says should not be in a video for a general audience. Turns out we often underestimate the large niche technical-but-not-specialist audience which doesn't mind things not being dumbed down too much.

It's a matter of incentives, having made such a video you no doubt have a good understanding of the time required to produce this kind of content. Even publishing clean, reproducible code, which should be the absolute minimum, takes a lot of time and is absolutely not rewarded. So when researchers have a choice between publishing two papers with no supplementary material or publishing a single one that is well documented, cleanly coded, with a blog post, a video explanation, etc... it's no question. With the current incentive structures the choice is made for you.

That's a noble practice but I think everyone should stick at what he does best, for a better overall efficiency. As long as you make your paper easily available, as another commenter said, another person can make it more comprehensible for the general public.

One of the causes of the slowdown (even if marginal) of science and research in general is the administrative and social media overlays that were added to them.

> As long as you make your paper easily available, as another commenter said, another person can make it more comprehensible for the general public.

I'm not sure you appreciate how hard this might be for someone who is not closely connected to a project.

The people who can do that reliably will have: a) the academic chops on a similar level of a peer reviewer b) social media skills. a) puts them back in the bracket of people you don't want to 'slow down'.

Well I agree but I see it like a pyramid. You don't have to worry about people at the bottom of the knowledge pyramid getting access to the last breakthrough in some field if they don't already know the basics about that field. They will naturally access it when they "climb" this pyramid of knowledge through more specialized sources or studies.

More over : the population of people who are good at doing something isn't necessarily the same as the one good at explaining it.

It's like saying Newton would have to spend 20% of his time explaining to 14yrs old kids what he's doing when someone less capable than him would do it as good but would leave Newton free for what he does best.

A typical computer systems research project takes two years, though many take a lot more. After several years research, we write a paper like it's 1920, spend a day knocking together some powerpoint slides, and give a 20-minute presentation at some conference (and those are the successful projects). Science, whether pure or applied, is about pushing forward the bounds of knowledge and then, crucially, communicating those insights. There are so many papers published these days - one of my papers has been cited over 10,000 times - that's an average of 1.5 times a day for 19 years straight. Seems unlikely most of those papers ever get read. If you still believe in the work once it's published, you really should do your best to communicate your excitement to others. Unless you made a huge breakthough (unlikely in any field), no-one else is going to learn from your insights otherwise.

Same with MOOCs I think. It's too bad most of them are so bad they are not worth taking, but the ones that are good (e.g. Andrew Ng's machine learning MOOC) are having insane impact even though most people don't finish them.

Reply on news.ycombinator.com