Scam journals will literally publish crap

In the last couple of years, researchers have started to experience an onslaught of invitations to attend scam conferences and submit papers to scam journals.  Many of these seem to emanate from the OMICS group of Henderson, NV and its various subsidiaries.  A couple of months ago I decided to start trolling these scammers, just to see if I could get a reaction.  After sending many of these, I finally got a response yesterday, which speaks to the complete lack of quality of these journals.  

This was the solicitation:

On May 20, 2016, at 12:55 AM, Abnormal and Behavioural Psychology <behaviouralpsychol@omicsinc.com> wrote: 

Dear Dr. Russell A. Poldrack,Greetings from the Journal of Abnormal and Behavioural Psychology
Journal of Abnormal and Behavioural Psychology is successfully publishing quality articles with the support of eminent scientists like you.
We have chosen selective scientists who have contributed excellent work, Thus I kindly request you to contribute a (Research, Review, Mini Review, Short commentary) or any type of article.
The Journal is indexed in with EBSCO (A-Z), Google Scholar, SHERPA-Romeo, Open J-gate, Journal Seek, Electronic Journals Library, Academic Keys, Safety Lit and many more reputed indexing databases. 

We publish your manuscript within seven days of Acceptance. For your Excellent Research work we are offering huge discount in the publishing fee (70%). So, we will charge you only 300 USD. This huge offer we are giving in this month only. 

...
With kind regards
Sincerely,
Joyce V. Andria

I had previously received exactly this same solicitation about a month ago, to which I had responded like this:

Dear Ms Andria, 

Thanks for your message.  I just spent three minutes reading and thinking about your email.  My rate for commercial consulting is $500/hour.  Can you please remit your payment of $25 to me at the address below?  I’m sure you can understand that the messages from your organization take valuable time away from scientists, and that you would agree that it’s only fair to renumerate us for this time.
I look forward to receiving your payment promptly.  If you do remit within 30 days I will be forced to send this invoice out for collection.
Sincerely,
Russ Poldrack

I got no response to that message.  So when I received the new message, I decided to step up my troll-fu:

Dear Ms. Andria,
Many thanks for your message soliciting a (Research, Review, Mini Review, Short commentary) or any type of article for your journal. I have a paper that I would like to submit but I am not sure what kind of article it qualifies as. The title is "Tracking the gut microbiome". The paper does not include any text; it is composed entirely of photos of my bowel movements taken every morning for one year. Please let me know if your journal has the capability to publish such a paper; I have found that many other journals are not interested.
Sincerely,
Russell Poldrack

Within 12 hours, I had a response:

From: Abnormal and Behavioural Psychology <behaviouralpsychol@omicsinc.com>
Subject: RE: Appreciated your Excellent Research work
Date: May 20, 2016 at 9:47:28 PM PDT
To: "'Russell Alan Poldrack'" <russpold@stanford.edu>
Dear Dr. Russell A. Poldrack,

Greetings from the Journal of Abnormal and Behavioural Psychology

Thank you for your reply.

I hereby inform you that your article entitled: “Tracking the gut microbiome” is an image type article.

We are happy to know that you want to publish your manuscript with us.

We are waiting for your  earliest submission.

We want to introduce your research work in this month to our Journal. We will be honored to be a part of your scientific journey.

Kindly submit your article on before 26th may, 2016.


Awaiting your response.,

With kind regards
Sincerely,
Anna Watson
Journal Coordinator
Journal of Advances in Automobile Engineering

There you have it: These journals will literally publish complete crap. I hope the rest of you will join me in trolling these parasites - post your trolls and any results in the comments.

Advice for learning to code from scratch

I met this week with a psychology student who was interested in learning to code but had absolutely no experience.  I personally think it’s a travesty that programming is not part of the basic psychology curriculum, because doing novel and interesting research in psychology increasingly requires the ability to collect and work with large datasets and build new analysis tools, which are almost impossible without solid coding skills.  

Because it’s been a while since I learned to code (back when programs were stored on cassette tapes), I decided to ask my friends on the interwebs for some suggestions.  I got some really great feedback, which I thought I would synthesize for others who might be in the same boat.  

Some of the big questions that one should probably answer before getting started are:

1. Why do you want to learn to code?  For most people who land in my office, it’s because they want to be able to analyze and wrangle data, run simulations, implement computational models, or create experiments to collect data.  
2. How do you learn best?  I can’t stand watching videos, but some people swear by them.  Some people like to just jump in and start doing, whereas others like to learn the concepts and theories first.  Different strokes...
3. What language should you start with?  This is the stuff of religious wars.  What’s important to realize, though, is that learning to program is not the same as learning to use a specific language.  Programming is about how to think algorithmically to solve problems; the specific language is just an expression of that thinking.  That said, languages differ in lots of ways, and some are more useful than others for particular purposes.  My feeling is that one should start by learning a first-class language, because it will be easier to learn good practices that are more general.  Your choice of a general purpose language should probably be driven by the field you are in; neuroscientists are increasingly turning to Python, whereas in genomics it seems that Java is very popular.  I personally think that Python offers a nice mix of power and usability, and it’s the language that I encourage everyone to start with.  However, if all you care about doing it performing statistical analyses, then learning R might be your first choice, whereas if you just want to build experiments for mTurk, then Javascript might be the answer.  There may be some problem for which MATLAB is the right answer, but I’m no longer sure what it is. A caveat to all of this is that if you have friends or colleagues who are programming, then you should strongly consider using whatever language they are using, because they will be your best source of help.
4. What problem do you want to solve?  Some people can learn for the sake of learning, but I find that I need a problem in order to keep me motivated.  I would recommend thinking of a relevant problem that you want to solve and then targeting your learning towards that problem.  One good general strategy is to find a paper in your area of research interest, and try to implement their analysis. Another (suggested by Christina van Heer) is to take some data output from an experiment (e.g. in an Excel file), read it in, and compute some basic statistics.  If you don't have your own data, another alternative is to take a large open dataset (such as health data from NHANES or an openfmri dataset from openfmri.org ) and try to wrangle the data into a format that lets you ask an interesting question.

OK then, so where do you look for help in getting started?

The overwhelming favorite in my social media poll was codeacademy.  It offers interactive exercises in lots of different languages, including Python.  Another Pythonic suggestion was http://learnpythonthehardway.org/book/ which looks quite good. 

For those of you who prefer video courses, there were also a number of votes for online courses, including those from Coursera:

• “Python for Everybody” 
• "An Introduction to Interactive Programming with Python"

EdX:

• Introduction to R for data science
• Harvard’s Introduction to Computer Science 

And  FutureLearn:

• Learn to Code for Data Analysis 

If you like video courses then these would be a good option.  

Other suggestions included:

• Learning statistics with R: A tutorial for psychologists and other beginners (free pdf book)
• http://pythontutor.com - this looks like a pretty cool tool to help see what a program is doing when it runs
• http://tryr.codeschool.com
• codemonkey (coding in a game environment)
• Swirl for R 
• Python for Vision Research
• Programming for Psychology in Python
• Datacamp
• lynda.com (commercial, but offers a free trial) 

Here are some suggested sites with various potentially useful tips

• Resources for Learning to Program using Python and Code Experiments Using Psychopy 
• Reading Python source code to improve programming skills
• Introduction to R
• 6 inspiring web sites that teach you to code
• Kendrick Kay's course on Statistics and Data Analysis in MATLAB
• Several people recommended Spyder as a development environment for Python (though I gave up on it because I found it to be too sluggish on the Mac)
• Here is a nice curated list of python tutorials for data science and machine learning
• 9 places you can learn how to code (for free)

Finally, it’s also worth keeping an eye out for local Software Carpentry workshops.

If you have additional suggestions, please leave them in the comments!