R-bloggers.com is now two years young. The site is an (unofficial) online R journal written by bloggers who agreed to contribute their R articles to the site.
In this post I wish to celebrate R-bloggers’ second birthmounth by sharing with you:

1. Links to the top 20 posts of 2011
2. Statistics on “how well” R-bloggers did this year
3. An invitation for sponsors/supporters to help keep the site alive

1. Top 24 R posts of 2011

R-bloggers’ success is largely owed to the content submitted by the R bloggers themselves.  The R community currently has almost 300 active R bloggers (links to the blogs are clearly visible in the right navigation bar on the R-bloggers homepage).  In the past year, these bloggers wrote over 2800 posts about R.

Here is a list of the top visited posts on the site in 2011:

1. How much of r is written in r
2. Cpu and gpu trends over time
3. Select operations on r data frames
4. Getting started with sweave r latex eclipse statet texlipse
5. Delete rows from r data frame
6. Amanda cox on how the new york times graphics department uses r
7. Hipster programming languages
8. Opendata r google easy maps
9. New r generated video has stackoverflow posting behavior changed over time
10. SNA visualising an email box with r
11. 100 prisoners 100 lines of code
12. Google ai challenge languages used by the best programmers
13. Basics on markov chain for parents
14. Top 10 algorithms in data mining
15. A million random digits review of reviews
16. Character occurrence in passwords
17. Setting graph margins in r using the par function and lots of cow milk
18. The new r compiler package in r 2 13 0 some first experiments
19. Tutorial principal components analysis pca in r
20. Making guis using c and r with the help of r net

2. Statistics – how well did R-bloggers do this year

There are several matrices one can consider when evaluating the success of a website.  I’ll present a few of them here and will begin by talking about the visitors to the site.

This year, the site was visited by over 665,000 “Unique Visitors.”  There was a total of over 1.4 million visits and over 2.8 million page-views.  People have surfed the site from over 200 countries, with the greatest number of visitors coming from the United States (~40%) and then followed by the United Kingdom (6.9%), Germany (6.6%), Canada (4.7%), France (3.3%), and other countries.

The site has received between 15,000 to 45,000 visits a week in the past few months, and I suspect this number will remain stable in the next few months (unless something very interesting will happen).

I believe this number will stay constant thanks to visitors’ loyalty: 55% of the site’s visits came from returning users.

Another indicator of reader loyalty is the number of subscribers to R-bloggers as counted by feedburner, which includes both RSS readers and e-mail subscribers.  The range of subscribers is estimated to be between 5600 to 5900.

Thus, I am very happy to see that R-bloggers continues to succeed in offering a real service to the global R users community.

3. Invitation to sponsor/advertise on R-bloggers

This year I was sadly accused by google adsense of click fraud (which I did not do, but have no way of proving my innocence).  Therefor, I am no longer able to use google adsense to sustain R-bloggers high monthly bills, and I turned to rely on direct  sponsoring of R-bloggers.

If you are interested in sponsoring/placing-ads/supporting R-bloggers, then you are welcome to contact me.

Happy new year!
Yours,
Tal Galili

I was recently reminded that the wonderful team at warwick University made sure to put online many of the slides (and some videos) of talks from the recent useR 2011 conference.  You can browse through the talks by going between the timetables (where it will be the most updated, if more slides will be added later), but I thought it might be more convenient for some of you to have the links to all the talks (with slides/videos) in one place.

I am grateful for all of the wonderful people who put their time in making such an amazing event (organizers, speakers, attendees), and also for the many speakers who made sure to share their talk/slides online for all of us to reference.  I hope to see this open-slides trend will continue in the upcoming useR conferences…

Bellow are all the links:

Tuesday 16th August

Lightning Talks

• Community and Communication, MS.02, Chair: Ashley Ford
• George Zhang: China R user conference [Slides]
• Tal Galili: Blogging and R – present and future [Link]
• Markus Schmidberger: Get your R application onto a powerful and fully-configured Cloud Computing environment in less than 5 minutes. [Slides]
• Eirini Koutoumanou: Teaching R to Non Package Literate Users [Slides]
• Randall Pruim: Teaching Statistics using the mosaic Package [Slides]
• Statistics and Programming, MS.01, Chair: Elke Thönnes
• Toby Dylan Hocking: Fast, named capture regular expressions in R2.14 [Slides]
• John C. Nash: Developments in optimization tools for R [Slides]
• Christophe Dutang: A Unified Approach to fit probability distributions [Slides]
• Package Showcase, MS.03, Chair: Jennifer Rogers
• James Foadi: cRy: statistical applications in macromolecular crystallography [Slides]
• Emilio López: Six Sigma is possible with R [Slides]
• Jonathan Clayden: Medical image processing with TractoR [Slides]
• Richard A. Bilonick: Using merror 2.0 to Analyze Measurement Error and Determine Calibration Curves [Slides]

Wednesday 17th August

Thursday 18th August

This is (roughly) the lightning talk I gave in useR2011. If you are a reader of R-bloggers.com then this talk is not likely to tell you anything new. However, if you have a friend, college or student who is a new useRs of R, this talk will offer him a decent introduction to what the R blogosphere is all about.

The talk is a call for people of the R community to participate more in reading, writing and interacting with blogs.

I was encouraged to record this talk per the request of Chel Hee Lee, so it may be used in the recent useR conference in Korea (2011)

The talk (briefly) goes through:

1. The widespread influence of the R blogosphere
2. What R bloggers write about
3. How to encourage a blogger you enjoy reading to keep writing
4. How to start your own R blog (just go to wordpress.com)
5. Basic tips about writing a blog
6. One advice about marketing your R blog (add it to R-bloggers.com)
7. And two thoughts about the future of R blogging (more bloggers and readers, and more interactive online visualization)

My apologies for any of the glitches in my English. For more talks about R, you can visit the R user groups blog. I hope more speakers from useR 2011 will consider uploading their talks online.

This post is a call for both R community members and R-bloggers, to come and help make The R Programming wikibook be amazing.

The R Programming wikibook is not just another one of the many free books about statistics/R, it is a community project which aims to create a cross-disciplinary practical guide to the R programming language.  Here is how you can join:

Dear R community member – please consider giving a visit to The R Programming wikibook.  If you wish to contribute your knowledge and editing skills to the project, then you could learn how to write in wiki-markup here, and how to edit a wikibook here (you can even use R syntax highlighting in the wikibook).  You could take information into the site from the (soon to be) growing list of available R resources for harvesting.

Dear R blogger, you can help The R Programming wikibook by doing the following:

• Write to your readers about the project and invite them to join.
• Add your blog’s R content as an available resourcefor other editors to use for the wikibook.  Here is how to do that:
  • First, make a clear indication on your blog that your content is licensed under cc-by-sa copyrights (*see what it means at the end of the post). You can do this by adding it to the footer of your blog, or by writing a post that clearly states that this is the case (what a great opportunity to write to your readers about the project…).
  • Next, go and add a link, to where all of your R content is located on your site, to the resource page (also with a link to the license post, if you wrote one).  For example, since I write about other things besides R, I would give a link to my R category page, and will also give a link to this post.  If you do not know how to add it to the wiki, just e-mail me about it (tal.galili@gmail.com).

If you are an R blogger, besides living up to the spirit of the R community, you will benefit from joining this project in that every time someone will use your content on the wikibook, they will add your post as a resource.  In the long run, this is likely to help visitors of the site get to know about you and strengthen your site’s SEO ranking.  Which reminds me, if you write about this, I always appreciate a link back to my blog

* Having a cc-by-sa copyrights means that you will agree that anyone may copy, distribute, display, and make derivative works based on your content, only if they give the author (you) the credits in the manner specified by you. And also that the user may distribute derivative works only under a license identical to the license that governs the original work.

———-

Three more points:

1) This post is a result of being contacted by Paul (a.k.a: PAC2), asking if I could help promote “The R Programming wikibook” among R-bloggers and their readers.   Paul has made many contributions to the book so far.  So thank you Paul for both reaching out and helping all of us with your work on this free open source project.

2) I should also mention that the R wiki exists and is open for contribution.  And naturally, every thing that will help the R wikibook will help the R wiki as well.

3) Copyright notice: I hereby release all of the writing material content that is categoriesed in the R category page, under the cc-by-sa copyrights (date: 20.06.2011), as long as the copied content comes with proper attribution which also  includes a link to the source of the article .  Now it’s your turn!

———-

List of R bloggers who have joined: (This list will get updated as this “group writing” project will progress)

• R-statistics blog (that’s me…)
• GETTING GENETICS DONE
• Struggling Through Problems
• Back side smack
• al3xandr3
• Cloudnumbers.com
• The R Tutorial Series blog
• …

For the most updated list, go to the resource page on the The R Programming wikibook.

Rob Calver wrote an interesting invitation on the R mailing list today, inviting potential authors to submit their vision of the next great book about R. The announcement originated from the Chapman & Hall/CRC publishing houses, backed up by an impressive team of R celebrities, chosen as the editors of this new R books series, including:

• John M. Chambers
• Torsten Hothorn
• Duncan Temple Lang
• Hadley Wickham

Bellow is the complete announcement:

————————————–
We are pleased to announce the launch of a new series of books on R.

Chapman & Hall/CRC: The R Series

Aims and Scope

This book series reflects the recent rapid growth in the development and application of R, the programming language and software environment for statistical computing and graphics. R is now widely used in academic research, education, and industry. It is constantly growing, with new versions of the core software released regularly and more than 2,600 packages available. It is difficult for the documentation to keep pace with the expansion of the software, and this vital book series provides a forum for the publication of books covering many aspects of the development and application of R.

• The scope of the series is wide, covering three main threads:
• Applications of R to specific disciplines such as biology, epidemiology, genetics, engineering, finance, and the social sciences.
• Using R for the study of topics of statistical methodology, such as linear and mixed modeling, time series, Bayesian methods, and missing data.
• The development of R, including programming, building packages, and graphics.

The books will appeal to programmers and developers of R software, as well as applied statisticians and data analysts in many fields. The books will feature detailed worked examples and R code fully integrated into the text, ensuring their usefulness to researchers, practitioners and students.

Series Editors

• John M. Chambers (Department of Statistics, Stanford University, USA; jmc@stat.stanford.edu)
• Torsten Hothorn (Institut f?r Statistik, Ludwig-Maximilians-Universit?t, M?nchen, Germany; torsten.hothorn@stat.uni-muenchen.de)
• Duncan Temple Lang (Department of Statistics, University of California, Davis, USA; duncan@wald.ucdavis.edu)
• Hadley Wickham (Department of Statistics, Rice University, Houston, Texas, USA; hadley@rice.edu)

Call for Proposals

We are interested in books covering all aspects of the development and application of R software. If you have an idea for a book, please contact one of the series editors above or one of the Chapman & Hall/CRC statistics acquisitions editors below. Please provide brief details of topic, audience, aims and scope, and include an outline if possible.

We look forward to hearing from you.

Best regards,

• Rob Calver (rob.calver@informa.com)
• David Grubbs (david.grubbs@taylorandfrancis.com)
• John Kimmel (john.kimmel@taylorandfrancis.com)

A year ago (on December 9th 2009), I wrote about founding R-bloggers.com, an (unofficial) online R journal written by bloggers who agreed to contribute their R articles to the site.

In this post I wish to celebrate R-bloggers’ first birthday by sharing with you:

1. Links to the top 14 posts of 2010
2. Reflections about the origin of R-bloggers
3. Statistics on “how well” R-bloggers did this year
4. Links to other related projects
5. An invitation for sponsors/supporters to help keep the site alive

1. Top 14 R posts of 2010

R-bloggers’ success is largely owed to the content submitted by the R bloggers themselves.  The R community currently has 143 active R bloggers (links to the blogs are clearly visible in the right navigation bar on the R-bloggers homepage).  In a little over one year, these bloggers wrote almost 3,000 posts about R.  That is amazing!

Here is a list of the top visited posts on the site in 2010:

• 100 Prisoners, 100 lines of code
• Google AI Challenge: Languages Used by the Best Programmers
• Getting Started with Sweave: R, LaTeX, Eclipse, StatET, & TeXlipse
• Why Use R?
• “simply start over and build something better”
• R Tutorial Series: R Beginner’s Guide and R Bloggers Updates
• Select operations on R data frames
• Hacker News User Base Changed?
• Top 10 Algorithms in Data Mining
• Fantasy football (oops, soccer)
• Delete rows from R data frame
• Visualizing Facebook Friends: Eye Candy in R
• Advanced graphics in R
• How to build a world-beating predictive model using R

2. Motivation for creating R-bloggers

Originally, the idea for R-bloggers came when, over a year ago, I spent several hours trying to find bloggers who wrote about R.  I was successful in finding roughly 14 R bloggers (and too many blog posts of people talking about pirates).  This experience led me to wonder how many other people like myself were also struggling to find these bloggers.  The second thought I had was the answer to the following question: “What can I offer an R blogger so that he will tell me that he exists?”  The answer I came up with is “audience and traffic” – and that’s what R-bloggers tries to achieve: the site offers the blogger audience and traffic in exchange for the blogger giving permission to republish their “R content” on the site.

Part of my motivation was that, as one of these bloggers who wrote about R (here, on R-statistics.com), I too hoped to gain more audience and traffic for my content.   R-bloggers helped me achieve this goal.

3. Statistics – how well did R-bloggers do this year

There are several matrices one can consider when evaluating the success of a website.  I’ll present a few of them here and will begin by talking about the visitors to the site.

This year, the site was visited by about 286,000 “Absolute Unique Visitors.”  There was a total of nearly 600,000 visits and over 1 million page-views.  People have surfed the site from over 200 countries, with the greatest number of visitors coming from the United States (40%) and then followed by the United Kingdom (6.8%), Germany (6.6%), Canada (4.9%), France (3.3%), and other countries.

The site has received between 15,000 to 25,000 visits a week in the past few months, and I suspect this number will remain stable in the next few months (unless something very interesting will happen).

I believe this number will stay constant thanks to visitors’ loyalty: 60% of the site’s visits came from returning users.

Another indicator of reader loyalty is the number of subscribers to R-bloggers as counted by feedburner, which includes both RSS readers and e-mail subscribers.  The range of subscribers is estimated to be between 2600 to 2900.

Thus it seems that R-bloggers succeeds in offering a real service to the R users community.

4. Projects related to R-bloggers

During the last year I have created several R-bloggers clone sites in the hopes of serving other audiences.  I started a multilingual version of R-bloggers at www.r-bloggers.com/lang/ (currently hosting 7 bloggers, written in Dutch, Indonesian, Italian, Korean, Russian, Spanish).  I hope more will join the site in the future.

I’ve also started 3 other promising such sites: SAS-x.com, DanceBloggers.com and forex-bloggers.com.  How will they do?  Only time will tell.

5. Invitation to sponsor/advertise on R-bloggers

Due to the increase in the site’s popularity, 4 months ago I had to upgrade R-bloggers’ hosting account to a VPS hosting, which had directed me to decide on attempting to add ads to R-bloggers so to keep the site self sufficient financially.

So in the hopes of keeping the site sustainable in the long run, I am now (somewhat forced) to make this call: if you are interested in sponsoring/placing ads/supporting R-bloggers, then you’re welcome to contact me.

Happy new year!
Yours,
Tal Galili

Update: the competition was just launched.
* * *

What is the competition about?

Drew Conway and John Myles Whyte have collected data from (52) R users about the packages they have installed. The data is now available on github for download and the contest will be run on the kaggle platform.

For more details, head over to dataists.

And for fun, here is the dependency graph for R packages they have assembled so far:

A tiny bit more on R bloggers virality

Since I started getting involved in the R bloggers community, I can recall two major discussion that have attracted more then two bloggers writing about them.

The first one was people in the R community arguing against Dr. AnnMaria De Mars post “The Next Big Thing”, where she wrote that “R is an epic fail.” (my response to it then was the post ““The next big thing”, R, and Statistics in the cloud“)
The second one was tackling the question “Is R “that bad” that it should be rewritten from scratch?”. Many responses went to the post by Ross Ihaka who was arguing for the need to rewrite R from scratch (a very wide spectrum of replies to that can be viewed on the stackoverflow discussion I started on the topic.)

And in the past few days I noticed a starting of a cascade of posts, all promoting the post at “dataists“.

This leads me to three simple statements:
1) I think it is beautiful that the R community has advocates that defend R’s role in the future of statistics
2) I think it is important that the R community has so many (smart) people (beyond the amazing R core team) who reflects on how R is doing, and of the challenges that the R language and environment will face in the future.
3) I think it is a fascinating thing that the R community is a community of researchers who have the skills to research themselves. Each community of a discipline can use it’s skill on itself – psychologists may psychoanalyze themselves, WordPress bloggers may write about WordPress, and R users can plan studies and analyse data about themselves – this potential is only beginning to be untapped – and I am excited to see where it might lead in the years to come.

Good news for R bloggers who are using WordPress.com to host their blog.

This week, the good people running WordPress.com (special thanks goes to Yoav Farhi), have added the ability for all the users of the WordPress.com platform to be able to highlight their R code inside posts.

Basically you’ll need to wrap the code in your post like this:

[sourcecode language="r"]
test.function = function(r) {
    return(pi * r^2)
}
test.function(1)
[/sourcecode]

(Which will then look like this:

)

Further details (and other supported languages) can be read about on this WordPress.com support page.

This new feature was possible thanks to the work of Yihui Xie (who create the famous cool animation package for R), who created a R syntax brush for the syntaxhighlighter WordPress plugin (the plugin used by WordPress.com for sytnax highlighting) . And thanks should also go to Andrew Redd, the creator of NppToR (which connects between notepad++ to R). He both made some good suggestions, and was game to take on the brush creation in case there would be problems, which thankfully so far there aren’t any)

p.s: If you are a WordPress.org users (e.g: have a self hosted WordPress blog) and want to enable R syntax highlighting for your blog, I would recommend the use of the WP-Syntax plugin (enhanced with GeSHi version 1.0.8.6) which can be downloaded here.

This post can be summed up by one two sentences: “We can’t buy love.” “Starting to pay for love could make it disappear” while at the same time “We need money to live and love”. These two conflicting forces, with relation to open source, are the topic of this post.

This post is directed to the community of R users but is relevant to people of all open source projects. It deals with the question of open source projects and funding. Specifically, should a community of open source developers and users, once it exists, want to start raising/donating money to the main code contributers?

The conflict arises when, on the one side, we intuitively wish to repay the people who have helped us but worry of the implications of behavioral studies that suggests that doing so might destroy the motivation of the developers to continue working without contently getting payed, and that making the shift from doing something for one reason (whatever it is) to doing it for money, might not easily be turned back.
On the other side, developers needs to make a (good) living, and we (as a community) should strive for them to be well payed.
How can these two be reconciled?

This article won’t offer a decisive conclusions – and my hope is to invite discussion on the matter (from both amatures and professionals in the field of open source and behavioral economics) so to give more ideas for people to base their opinions on.

Update: this post was substantially updated from it’s original version, thanks to responses both in the comments, and especially in the e-mails. I apologies for writing a post that had needed so many corrections, and at the same time I am grateful for all the people who took the time to shed light in places where I was wrong.

* * * *

Motivation: R has issues – how do we get them fixed?

In the past two weeks there has been a raging debate regarding the future of R (hint: “what is R“). Without going deeper into the topic (I already wrote about it here, where you too can go and respond), I’ll sum up the issue with a quote from Ross Ihaka (one of the two founders of R) who recently wrote:

I’ve been worried for some time that R isn’t going to provide the base that we’re going to need for statistical computation in the future. (It may well be that the future is already upon us.) There are certainly efficiency problems (speed and memory use), but there are more fundamental issues too. Some of these were inherited from S and some are peculiar to R.

After this, several discussion threads where started around the web (for example: 0, 1, 2, 3, 4 ,5, 6 ), but then a comment was made in the R-help mailing list by Jaroslaw Piskorski who wrote:

A few days ago Tal Galili posted a message about some controversies concerning the future of R. Having read the discussions, especially those following Ross Ihaka’s post, I have come to the conclusion, that, as usual, the problem is money. I doubt there would be discussions about dropping R in its present form if the R-Foundation were properly funded and could hire computer scientists, programmers and statisticians. If a commercial company is able to provide big-database and multicore solutions, then so would a properly founded R-Foundation.

To which my response is that: I strongly disagree with this statement..
That is, I do agree that money could help with things. It could be that money could be a part of the solution. But I doubt that the core of this problem is money. Nor that it would be solved if we could only now hire “computer scientists, programmers and statisticians” (although that could be part of the solution).

And the reason I am doubtful stems from two sources:

1. Motivation in general – and money

The first reason is presented in the following short (~10 minutes) video titled “Drive: The surprising truth about what motivates us”, adapted from Dan Pink’s talk at the RSA.
This talk dicusses what motivates us, and also about what (surprisingly) doesn’t motivate us: money. What does? watch the talk (it’s fun):

2. The split personality of open-source developers: Social Norms vs Market Norms

The second concern I have comes after reading Dan Ariely’s great book “Predictably Irrational”. In chapter 4, Ariely makes the distinction between (what he terms) “Social Norms” and “Market Norms”. You can listen to him talk about it in the following (~4 minutes) video:

Another example of what is said in this video is an experiment Dan made where he took three groups for a 5-minute task on a computer, dragging circles into a square. One group did it as a favor to the experimenter, one group was paid $5 and the third group was paid 50 cents. The 50-cent group was less productive than the $5 group. But the people who did the task as a favor were the most productive of all! In case this artificial experiment is not convincing, Dan also gave real-life examples, including military service and the pro bono work of lawyers.

In our case, we can often teach R in the University or use it to solve real world problems while getting paid (and being expected to be paid), but at the same time we ask and give help (answering questions and programming) online (and offline with friends) for free. We are walking a thin line of keeping a psychological balance here. Ariely wrote that:

When a social norm collides with a market norm, the social norm goes away for a long time. In other words, social relationships are not easy to reestablish.

And as Stormy Peters (executive director of the GNOME Foundation) wrote:

One of the things about the open source community that continues to baffle those non-open source people is, “why do you do it?” Open source developers work on open source software for a number of reasons from scratching an itch to gaining a reputation to building a resume to contributing to a good cause.

The interesting problem comes when money enters into the equation. Research shows that when someone works on something for free (for internal rewards) if you start paying them you replace those internal rewards. Then if you stop paying them, they will stop working on it. Does that hold true for open source software? Are commercial companies killing open source by paying people to work on it?

Or said differently (and elsewhere):

Once you are paid to work on open source software, it would be hard to go back to doing it for free.

Hence my question (and fear): Would starting to pay people in the R community (who by now where working for free) to work on R (a free open source project) – will end up killing it?

So can we pay open source developers?

Let’s be clear here – we can pay open source developers, but this includes the risk of later loosing them from the community. Would this always be the case – I don’t know (hence the room for discussion at the end of the post).

The answer: Love
One thing I do believe we should do is to be grateful: Send developers kind e-mails, buy their books, link to their blogs/home-pages – show them we love their work. Why am I using the “L” word? Because open source is (as Clay Shirky convinced me in his ~9 minutes video) is about Love:

And in the context of R:
The quality of R would not have been made possible even if all the people who have worked for it where to pay the developers from day 1. I am saying this again: If we where forced to pay to have R developed for us, it would have been more expansive then we could have been able to ever afford (under market norms). Since some of the best statisticians in the world (please correct me if I am wrong), have spent countless hours (days/months/years) to make this software work and support it’s user base, can you imagine how much money that would have cost?

So is money evil for open source?

Answer (IMHO): no!

Money, like a knife, is a tool – not good nor evil.

On the one hand, switching from community appreciation to rewarding with money might turn out to be a dangerous path for the future of R.

At the same time I believe (and I am willing to be proven wrong) that we SHOULD get money collected to our community, and that we should use it to pay people outside our community: graphic designers, UI people, CS students (who are not very deep into the R world), grants for young students and maybe even paying the R developers core team. My current rule of thumb will be that money should be used only mostly to get skills that are outside of our current community base.

Learning from the experience of other FOSS projects

The questions this post reflects upon are relatively new to us (e.g: how to scale up social relationships in collaboration projects). One of our best sources for solutions is probably the experience of other open source projects. While history may not predict our future, it can still give us ideas and even inspire us of what can be done.

I hope to link here to posts on the topic, if you have any, please link to them in the comments.

(Originally I wrote about WordPress, but after getting responses from some friends closer to the core team – I decided to remove that section so to not misinform people)

I’ll conclude

I don’t think R developers should be paid. (this is not exact and I erased this sentence)
I believe money should be collected by the community for the community.
Paying R developers is tricky, I don’t know how it can be done in a healthy and stable way (although I believe it can be done).
A good strategy for spending community’s money could be to pay for services that are outside our community knowledge/skill base.

Your opinions are welcomed.

At the useR!2010 conference I had the honor of giving a (~15 minute) talk titled “Blogging about R”. The following is the abstract I submited, followed by the slides of the talk and the audio file of a recording I made of the talk (I am sad it got a bit of “hall echo”, but it’s still listenable…)

P.S: this post does not absolve me from writing up something (with many thanks and links to people) about the useR2010 conference, but I can see it taking a bit longer till I do that.

—————–

Abstract of the talk

This talk is a basic introduction to blogs: why to blog, how to blog, and the importance of the R blogosphere to the R community.

Because R is an open-source project, the R community members rely (mostly) on each other’s help for statistical guidance, generating useful code, and general moral support.

Current online tools available for us to help each other include the R mailing lists, the community R-wiki, and the R blogosphere. The emerging R blogosphere is the only source, besides the R journal, that provides our community with articles about R. While these articles are not peer reviewed, they do come in higher volume (and often are of very high quality).

According to the meta-blog R-bloggers.com, the (English) R blogosphere has produced, in January 2010, about 115 “articles” about R. There are (currently) a bit over 50 bloggers (now about 100) who write about R, with about 1000 (now ~2200) subscribers who read them daily (through e-mails or RSS). These numbers allow me to believe that there is a genuine interest in our community for more people – perhaps you? – to start (and continue) blogging about R.

In this talk I intend to share knowledge about blogging so that more people are able to participate (freely) in the R blogosphere – both as readers and as writers. The talk will have three main parts:

• What is a blog
• How to blog – using the (free) blogging service WordPress.com (with specific emphasis on R)
• How to develop readership – integration with other social media/networks platforms, SEO, and other best practices

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Tal Galili founded www.R-bloggers.com and blogs on www.R-statistics.com
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Audio recording of the talk

Click here to download the audio file

(I apologies for the, sometimes, unclear recording – and hope you will still find the talk to be of some use to you)

Slides

Download (PDF, 5.09MB)