RichardPrice

San Francisco, CA. Full time.

Academia.edu is a social platform for academics to share research papers. The company's mission is to accelerate the world's research. 4.1m academics have joined Academia.edu, and over 300k join each month.

Many people believe that science is too closed, and too slow. We are trying to make science faster and more open. There are 4 things we are trying to achieve with Academia.edu:

- Instant distribution. Right now there is a 12 month time-lag between submitting a paper to a journal, and the paper being published. We need to make publishing a button, and the distribution of scientific ideas instant.

- Better peer review. Currently two people peer review a paper, which is too small a sample size. With 50,000 people worldwide in a research community like Machine Learning, or breast cancer, what 2 people think is not statistically significant. We need a broader-based peer review process, one that surfaces the opinions from the entire scientific community.

- Data-sets. Scientists don't share their data-sets right now. The data remains stuck on their hard-drives. The main reason for this is a lack of incentives for the scientists to share their data. We need to introduce the right reputation mechanisms in science to facilitate the sharing of data. -

- Open access. We need to bring about a world where a villager in India has the same access to the world’s scientific output as a professor in Harvard. When you open up access to the world’s scientific literature to the 2.5 billion people who are online right now, magical things can happen.

We're a 12-person engineering-driven team based in downtown San Francisco. Technologies we use include Rails, PostgreSQL, Redis, Varnish, Solr, Memcached, and Mongodb.

We have raised $6.7 million from Spark Capital, True Ventures, Mark Shuttleworth (founder of Ubuntu), and others. We are looking to hire software engineers to help build a faster and more open science.

There is more information about the company on our hiring page, at http://academia.edu/hiring. There is more on TechCrunch about our mission here http://techcrunch.com/2012/02/05/the-future-of-peer-review/ (The Future of Peer Review) and here http://techcrunch.com/2013/02/03/the-future-of-the-scientifi.... (Reputation Metrics in Science)

We will handle re-location, including visas. We are not currently hiring remote employees.

If you are interested to learn more, please email Richard Price at richard [at] academia.edu.

San Francisco, CA. Full time.

Academia.edu is a social platform for academics to share research papers. The company's mission is to accelerate the world's research. 3.7m academics have joined Academia.edu, and over 300k join each month.

Many people believe that science is too closed, and too slow. We are trying to make science faster and more open. There are 4 things we are trying to achieve with Academia.edu:

- Instant distribution. Right now there is a 12 month time-lag between submitting a paper to a journal, and the paper being published. We need to make publishing a button, and the distribution of scientific ideas instant.

- Better peer review. Currently two people peer review a paper, which is too small a sample size. With 50,000 people worldwide in a research community like Machine Learning, or breast cancer, what 2 people think is not statistically significant. We need a broader-based peer review process, one that surfaces the opinions from the entire scientific community.

- Data-sets. Scientists don't share their data-sets right now. The data remains stuck on their hard-drives. The main reason for this is a lack of incentives for the scientists to share their data. We need to introduce the right reputation mechanisms in science to facilitate the sharing of data. -

- Open access. We need to bring about a world where a villager in India has the same access to the world’s scientific output as a professor in Harvard. When you open up access to the world’s scientific literature to the 2.5 billion people who are online right now, magical things can happen.

We're a 12-person engineering-driven team based in downtown San Francisco. Technologies we use include Rails, PostgreSQL, Redis, Varnish, Solr, Memcached, and Mongodb.

We have raised $6.7 million from Spark Capital, True Ventures, Mark Shuttleworth (founder of Ubuntu), and others.

We are looking to hire software engineers to help build a faster and more open science.

There is more information about the company on our hiring page, at http://academia.edu/hiring. There is more on TechCrunch about our mission here http://techcrunch.com/2012/02/05/the-future-of-peer-review/ (The Future of Peer Review) and here http://techcrunch.com/2013/02/03/the-future-of-the-scientifi... (Reputation Metrics in Science)

We will handle re-location, including visas. We are not currently hiring remote employees.

If you are interested to learn more, please email Richard Price at richard [at] academia.edu.

Agreed. There are many aspects to changing the scientific ecosystem in such a way that sharing data-sets is the default, not the exception.

My sense is that the most critical aspect here is the incentives aspect. I think if sharing data-sets can enhance a scientist's reputation, and make it easier for them to demonstrate to grant committees that they have had an impact on the field, scientists will put in the work to curate and share data-sets.

If your papers are already on Academia.edu, and that is where you share your research output, it's useful to be able to share your data-sets and code too.

Of course that doesn't prevent you from uploading data to other places on the web, such as the site you mention...

You're right to focus on rewards. The rewards have to be there for academics to share their data-sets and code. The feedback loop needs to be closed, so that if you share your data, and that data has an impact, that impact is reflected back on you. You can then take that impact and show it to your tenure/grant committee, who can reward you for it. There are a bunch of startups, Academia.edu being one of them, that are very focused on closing that feedback loop.

Mendeley and ResearchGate are both great companies, but if you look at Quantcast/Compete/Alexa, you'll see that Academia.edu is noticeably larger than them in traffic. Academia.edu also has more users. I'm sorry to hear that Academia.edu doesn't satisfy your use-case though....

Do you mean having a reputation system on Wikipedia, or the ability to put data-sets on Wikipedia?

Currently 75% of the world's scientific data isn't shared. http://codata2012.tw/news/75-of-research-data-is-never-made-...

The main reason for that is that there is an established reputation system for papers, namely journals, but there isn't one for content formats that aren't papers - data-sets, code, videos, images etc.

Part of what Academia.edu is doing is building a new reputation system in science based on audience metrics: how many people have read your papers, from which countries; how many followers you have etc. We are then attaching various kinds of scientific media to that reputation system in order to accelerate sharing.

The idea is that if you can build your reputation by sharing your data-sets, you're likely to consider doing it.

Another dimension to sharing data-sets along with papers is that papers with data-sets attached get more citations http://www.plosone.org/article/info:doi%2F10.1371%2Fjournal....

Readers prefer papers with data-sets attached to them, because you can check the data and see how the conclusions of the paper stand up. That preference may be part of what drives the higher citation rates.

Authorea is a great project. I love the idea of helping academics write their papers natively for the web. Good luck Nate and Alberto!

You're right that the cost isn't the main issue. It shouldn't be disregarded though: with 2 million articles published a year, a $2,000 cost per article means $4 billion a year that could be spent on more research. To put that in context, the NIH's budget for tackling cancer is $4.9 billion a year.

The main issues with the journal system are the effects it has on the speed and quality of scientific communication. Peer review by two people is not robust, and it is very slow; secondly, the full range of scientific media aren't shared.

These are the problems that, I believe, require an overhaul of the reputation system in science. The only way to incentivize scientists to share their comments on papers quickly, and at scale, is to provide rewards for them to do that.

The range of media that scientists will start to share will be shared on platforms designed for that media type. Code will be shared on Github. Videos will be shared on YouTube. Data-sets will be shared on sites like Figshare or other sites dedicated to handling that content format well.

I believe that the two problems you mention, about peer review taking so long, and mathematicians not generally commenting much online, can be solved with reputation metrics.

The reason scientists don't blog a lot, or comment on blogs, is that there aren't reputation metrics associated with that kind of contribution to the scientific canon. It is the same reason that scientists don't share their data-sets. It is work to blog, and to prepare data-sets for public consumption, and there is no reward. If we reward scientists for sharing their comments on each other's papers, and for sharing data-sets, more scientists will be incentivized to make these kinds of contributions to the scientific canon.

The same goes for speed. When the journal editor asks a scientist to peer review a paper, the scientist accepts the request out of a sense of social obligation, but immediately that job goes to the bottom of her list of priorities. She will get no credit for doing the peer review, and so there is no reason to do it quickly.

This de-prioritization of peer review slows down the whole scientific communication system. To speed it up, we need to incentivize scientists to share their comments quickly. If someone sees something wrong the description of an experimental set-up, the system needs to be set up in such a way that they are incentivized to share that insight quickly.

With the time-lag, you have to take into account the rejection rate. Most articles don't get into their first choice journal, and perhaps get into their second or third choice. You can't parallel submit, meaning that the time-lag between finishing the paper, and it getting published in a journal, often ranges between 6 and 18 months.

I understand that Computer Science does have a slightly faster peer review process than other fields. Here is a piece where a leading neuroscientist writes "Today the lag [in my field] between submission and acceptance is often more than a year". http://www.pnas.org/content/early/2013/01/25/201300924.short...

Gamification is an important issue. You should note that the journal's peer review system, based on two people reading a paper, gets gamed. There is the wide-spread practice of defensive citation, where you defensively cite anyone who might conceivably peer review your paper, in order to maximize the chances of its getting accepted. Some people know how to play that game better than others.

One way of handling gamification is to look at the quality of the people interacting with a piece of content, and not just the quantity. This is how Google's PageRank algorithm deals with the issue.

There is also the approach, taken by Twitter and Facebook, of picking out the people's whose judgements you trust, and then letting them act as quality filters. Those systems can be gamed too, but aren't typically gamed to a large extent.

Open access journals, based on authors paying $1,000-$3,000 to publish a paper, are going to be a temporary stepping stone on the way to the decline of the journal.

We need new reputation metrics to encourage the sharing of data-sets, videos, code, and generally the full range of a scientist's output. 75% of the world's scientific data doesn't get shared because the rewards aren't there for the scientist to share it. Journals aren't going to start publishing data-sets (or code, or videos, or blog posts), and so we need new reputation metrics, and reward systems, to encourage scientists to share this kind of information.

The other problem with the journal system is that the peer review system is slow and surfaces the opinions of only two or three scientists about a given paper. If you have a community of 20,000 people in the DNA sequencing research community, asking two people what they think about a paper is not going to deliver a statistically significant result. Furthermore the typical time-lag for the system to surface those opinions is 12 months.

We need a more robust peer review system which surfaces opinions from the entire scientific community in real time. Reputation metrics are the key to building that system. We need to provide the rewards for scientists to share their comments on papers, so they can build their reputations off the insights they share on each other's papers.

Yes, that's true. But authors only started including their inbound citation counts on their job applications in the last few years.

I think the main reason for this is that Google Scholar's citation metrics were free and openly accessible, and the Science Citation Index was, and still is, behind expensive paywalls. Scientists were happier to include citation metrics in their resumes when they knew that the committee could easily check them, and wouldn't have to pay to get access to them.

You're right that the central challenge here is helping academics evaluate each other's work without relying so heavily on journal titles, closed access journals or otherwise. There is some movement here. Increasingly hiring committees are taking other reputation metrics into account when evaluating work (inbound citation counts, readership metrics, follower counts - anything that may make the job of an evaluation committee a little bit easier).

The fact that papers you are looking for tend to be available on author's webpages is atypical. A very small percentage of the 2 million papers published each year is available online for free. Institutions pay $8 billion a year to subscribe to journals, and they would be only too glad to cancel those subscriptions if they could.

Anyone can read the entire article in the browser on Academia.edu without logging in or registering. The paper is displayed using HTML5 in the browser, and there is no need to register to read the full text of the article.

We require people to register if they want to download a local copy of the paper. Registering takes a few seconds, and is free. Our users don't mind doing it.

Academia.edu's philosophy here is somewhat similar to BitTorrent's. With BitTorrent, if you want to download chunks of a file, you need to be uploading the same chunks to other people, and that is how the content and the community is sustained.

By requiring people to register to download articles, scientists are more likely to come back to Academia.edu and upload their own articles, increasing the number of open access articles on the web in general.

You don't have to be a member of a research institution. On the signup page, there is a checkbox to sign up as an independent researcher. See this screenshot http://cl.ly/image/1k2L0u1J1D3L

It's a good question. I expect that the Office of Science and Technology is working on it to some extent, but I am not aware of how deep their efforts are.

The basic idea is that the research papers should be open access 6 months after publication. 6 months is enough for publishers to recoup their costs of publication.

The reality is that publishers make all their money from site licenses. Harvard, e.g., will spend $15 million a year on subscriptions to various publishers like Elsevier, in return for access to all the new papers, and the back catalog.

Most papers that are downloaded, around 80%, are from the back catalog anyway, meaning that universities are incredibly price insensitive with respect to site license subscriptions. Journals could offer the new papers for free, and still universities would pay for the site license subscription.

This is what has happened with the arxiv: most new papers in theoretical physics are on there for free, and yet physics departments still subscribe to the theoretical physics journals. Why is that? It's because the departments need access to papers in the back catalog, which are not on the arxiv.

The upshot of this is that site license revenue wouldn't be affected by requiring open access on research 6 months after publication (or even 3 months, or 0 months, in my view). There is enough price insensitivity in the system for existing revenues to be unaffected by a change like this.

The reason the journal industry hates legislation like this, despite it not posing an economic danger to them, is that they are worried about the general trend of the government getting involved in changing the scientific publishing industry.

The journal industry would like to freeze their business model in the form that it was in during the pre-internet days. They believe that it's in their interest to fight every piece of pro-change legislation that the government suggests, in order to slow down the rate of change.

In practice that death star response probably only took an hour or two to write. However, figuring out federal policy on research is really tricky, and there are many stakeholders.

The fundamental problem is that the White House would like all research to be open, but every time they take any steps in that direction, they get whacked over the head in the media by the journal industry, and get called job-killers. The journal industry's argument is that any attempt to open up research will reduce their revenues, and kill jobs.

The view of most people in this debate is that the journal industry makes far too much money off research, and therefore the size of the industry should be reduced. But in this economic context being branded as a job killer is toxic.

The White House really wants to turn the debate around, and argue that open access for research is a stimulus for jobs: it will create more jobs, not fewer. To argue for that requires marshaling arguments and data from the private sector to establish that if people have access to federally-funded research, that will help them in their lives, and those benefits will outweigh the costs that the journal industry may experience.

Academia.edu was very active in working with the White House to spread the word about this petition when it first came out, and getting signatures for the petition to hit the 25k threshold.

The White House hasn't responded to it because initially they were busy with the election, and then with the fiscal cliff, and now with gun reform. Getting more signatures on the petition now will help them see that people care about this topic.

We plan to monetize via charging R&D firms for access to 'trending research' data - data about which papers are trending in a given area of research. I am a firm believer that the participants in the scientific community, and the world in general, should not pay to share or access research. Participants on Facebook, Twitter, Wordpress, and other sites don't pay to share ideas, and the same should be true of the way science works.

That said it would be unwise at this stage to rule out some kind of freemium option. It is not the ideal option, but when trying to achieve a mission you want to keep as many options open as possible. You don't want to box yourself in in ways that may damage you later. There are also many good freemium services (Github, Dropbox, LinkedIn).

To achieve a revolution in science, you need to build a huge community, and change the behavior of scientists. There are many ways in which a site tries to grow. Requiring users to sign up to download papers is one of those growth channels for us. If it was a big deal amongst our users, we would change it. But in practice it hasn't been an issue; our users don't mind this. Most people read the HTML5 version that is displayed in the browser. If they have to register to get a local copy of the paper, instead of paying $35 to get it from a journal, they don't mind that. Over 2 million academics have signed up, and we have about 4.5 million monthly unique visitors, so we have a fair amount of data on this.

Many people are discussing the future of research sharing right now. As one of the largest platforms on the web for sharing research, and since someone submitted this link (not me), it seems appropriate to give our view on how we think about the future of science.

We are working tirelessly on achieving this mission, and appreciate the interest and the feedback.

Opening up research is a critical part of Academia.edu's mission. There are four things we are trying to achieve with Academia.edu - ways in which we want to re-shape science.

- Instant distribution. Right now there is a 12 month time-lag between submitting a paper to a journal, and the paper being published. We need to remove that time-lag and introduce instant distribution of scientific ideas.

- Better peer review. Right now the peer review process takes 12 months to complete, and only surfaces the opinions of two academics - academics who may be biased, uninformed about the subject area, or just in a bad mood when writing the review. 2 people is too small a sample size. We need a faster and more robust peer review system, one that surfaces the opinions of the entire scientific community, and in real-time.

- Multi-media. Right now, scientists only share papers in PDF form. We need to bring about a science where scientists are incentivized to share data-sets, code, videos, blog posts, and comments on all these media. Right now a lot of the world’s scientific output does not get shared, because the system of credibility metrics only rewards one kind of format, the paper. We need to change this.

- Open access. We need to bring about a world where a villager in India has the same access to the world’s scientific output as a professor in Harvard. When you open up access to the world’s scientific literature to the 2.5 billion people who are online right now, magical things may happen.

Critical to achieving change in science is understanding how the reputation system works. Competition for funding is intense, and scientists optimize for the kinds of reputation metrics that the funding bodies and hiring committees check for. To achieve instant distribution, better peer review, multi-media sharing, and open sharing, one has to build reputation metrics that encourage that kind of activity.

Historically the main reputation metric in science has been the journal title. But over the last 4-5 years, new reputation metrics have emerged in science. Google Scholar pioneered the citation count: it released the count of how many inbound citations your work has received, and scientists started to take that metric and say to their funding committees 'this metric reflects well on me; I would like you to take it into account when evaluating my work'.

Academia.edu has been pioneering the introduction of usage metrics: page view counts for your papers. Our users regularly take screenshots of their Analytics Dashboard on Academia.edu and submit them to their tenure committees and funding bodies. There is a good case of someone including their Academia.edu Analytics in their application for tenure here http://blog.academia.edu/post/23302130233/user-spotlight-tim....

In the future there will be a family of reputation metrics in science, each reflecting a different aspect of impact.

If you are excited about building this future of science, we are looking for passionate people to join us. More about the company is here http://academia.edu/hiring. Send me an email at richard[at]academia.edu if you would like to chat further.

San Francisco, CA. Full time. Remote is fine too.

Academia.edu is a social platform for academics to share research papers. The company's mission is to accelerate the world's research.

Many people think that science is too closed, and too slow. We are trying to change that. There are 4 things we are trying to achieve with Academia.edu - ways in which we are trying to re-shape and accelerate science:

- Instant distribution. Right now there is a 12 month time-lag between submitting a paper to a journal, and the paper being published. We need to remove that time-lag and introduce instant distribution of scientific ideas.

- Better peer review. Right now the peer review process takes 12 months to complete, and only surfaces the opinions of two academics - academics who may be biased, uninformed about the subject area, or just in a bad mood when writing the review. 2 people is too small a sample size. We need a faster and more robust peer review system, one that surfaces the opinions of the entire scientific community, across a variety of dimensions, and in real-time.

- Multi-media. Right now, scientists only share papers in PDF form. We need to bring about a science where scientists are incentivized to share data-sets, code, videos, blog posts, and comments on all these media. Right now 50% or more of the world’s scientific output does not get shared, because the system of credibility metrics only rewards one kind of format, the paper. We need to change this.

- Open access. We need to bring about a world where a villager in India has the same access to the world’s scientific output as a professor in Harvard. When you open up access to the world’s scientific literature to the 2.5 billion people who are online right now, magical things may happen.

It's an exciting time for science. Science is transitioning from a 17th century way of sharing ideas, based on the journal system, to a faster system of sharing ideas on the web. Science is a foundational part of global growth: almost every innovation in medicine and technology has its roots in a science paper.

We need talented and passionate engineers to help us accelerate science. We have made a good start: 1.9 million academics have joined Academia.edu, and 4,000 join each day.

We're a 12 person, engineering-driven, team based in downtown San Francisco. Technologies we use include Rails, PostgreSQL, Redis, Varnish, Solr, Memcached, Mongodb, Beanstalkd. We have raised $6.7 million from Spark Capital, True Ventures, Mark Shuttleworth (founder of Ubuntu), and others.

Familiarity with our technologies is a plus, but it's not essential. It's far more important that you are a quick learner who can pick up new technologies quickly. We are looking to hire a range of positions:

* full stack engineers * growth engineer (optimizing our growth and retention channels) * iOS engineer

There is more information about the company on our hiring page, at http://academia.edu/hiring. There is more on TechCrunch about our mission here http://techcrunch.com/2012/02/05/the-future-of-peer-review/ (The Future of Peer Review) and here http://techcrunch.com/2012/04/29/the-future-of-science/ (The Future of Science)

We want to hire world class engineers. We want you to join us in building the future of science whether you are based in San Francisco, New York, Delhi, or Beijing. Remote work is fine. We will handle re-location, including visas, if you would like to re-locate, but re-location is not necessary.

If you are interested to learn more, please email Ryan Jordan at ryanj [at] academia.edu

San Francisco, CA. Full time. Remote is fine too.

Academia.edu is a social platform for academics to share research papers. The company's mission is to accelerate the world's research.

Many people think that science is too closed, and too slow. We are trying to change that. There are 4 things we are trying to achieve with Academia.edu - ways in which we are trying to re-shape and accelerate science:

- Instant distribution. Right now there is a 12 month time-lag between submitting a paper to a journal, and the paper being published. We need to remove that time-lag and introduce instant distribution of scientific ideas.

- Multi-media. Right now, scientists only share papers in PDF form. We need to bring about a science where scientists are incentivized to share data-sets, code, videos, blog posts, and comments on all these media. Right now 50% or more of the world’s scientific output does not get shared, because the system of credibility metrics only rewards one kind of format, the paper. We need to change this.

- Open access. We need to bring about a world where a villager in India has the same access to the world’s scientific output as a professor in Harvard. When you open up access to the world’s scientific literature to 2 billion people, magical things may happen.

- Better peer review. Right now the peer review process takes 12 months to complete, and only surfaces the opinions of two academics - academics who may be biased, uninformed about the subject area, or just in a bad mood when writing the review. 2 people is too small a sample size. We need a faster and more robust peer review system, one that surfaces the opinions of the entire scientific community, across a variety of dimensions, and in real-time.

It's an exciting time for science. Science is transitioning from a 17th century way of sharing ideas (sending papers around the world with 12 month time-lags in every iteration) to a much faster system of sharing ideas on the web. Science is a foundational part of global growth: almost every innovation in medicine and technology has its roots in a science paper.

We need talented and passionate engineers to help us accelerate science. We have made a good start: 1.8 million academics have joined Academia.edu, and 4,000 join each day.

We're a 12 person, engineering-driven, team based in downtown San Francisco. Technologies we use include Rails, PostgreSQL, Redis, Varnish, Solr, Memcached, Mongodb, Beanstalkd. We have raised $6.7 million from Spark Capital, True Ventures, Mark Shuttleworth (founder of Ubuntu), and others.

Familiarity with our technologies is a plus, but it's not essential. It's far more important that you are a quick learner who can pick up new technologies quickly. We are looking to hire a range of positions:

* full stack engineers

* growth engineer (optimizing our growth and retention channels)

* iOS engineer

There is more information about the company on our hiring page, at http://academia.edu/hiring. There is more on TechCrunch about our mission here http://tcrn.ch/T42VWC (The Future of Peer Review) and here http://tcrn.ch/R6Pgrr (The Future of Science)

We want to hire world class engineers. We want you to join us in building the future of science whether you are based in San Francisco, New York, Delhi, or Beijing. Remote work is fine. We will handle re-location, including visas, if you would like to re-locate, but re-location is not necessary.

If you are interested to learn more, please email Ryan Jordan at ryanj [at] academia.edu

Reluctant to provide an example? In my comment above I said that all the companies at the conference were examples of effective growth teams.

I suggest that we respectfully agree to disagree.

An amusing quote, but I don't think Zuckerberg, Dorsey, Pincus, and the CEOs of the other companies are all being deceived by fatter lines on a graph!

Every company at the conference was an example of the effectiveness of growth teams. Facebook, LinkedIn, Zynga, Twitter and so on have all found that being rigorous about optimizing their growth models has increased growth and engagement.

They were also at pains to mention that you cannot A/B test your way to a great product. You need deep insight and intuition to build a great product. But once you have a great product, you can help it grow faster by being rigorous about optimizing the drivers of growth.

It's a good question. You need to find a leading indicator that really is causal of engagement, and not just tangentially correlated with it.

Chamath stressed how critical it is to both minimize the time it takes to deliver a user their first 'Aha' moment, and then to continue to deliver those moments as regularly as possible. Presumably how many friends you have is causal, to some degree, of those 'Aha' moments - I expect that many of the 'Aha' moments on FB are to do with seeing cool content from your friends.

Nabeel also mentioned that it's also important to have various KPI metrics that you are aware of. His view was that there should be one over-arching operational metric that is broadly predictive of future engagement, and that the growth team should focus on that, but that, for any given tactic that you try out, you should be aware of its effect on a number of KPIs.