Why Articles on Social Media about Programming for Data Science Seem to Be Straight Out of a Time Capsule

Introduction
Data science related topics sell, no doubt about that. This is great is you are interested in the field and want to learn more about it, especially practical things that can offer you some orientation in the field. Since programming is a key component of data science, it makes sense to pay attention to material along these lines, particularly if you are new to this whole matter. 

How the Situation Is Today
Fortunately there is an abundance of articles on this topic, especially on the social media. However, not everyone who writes such articles is up-to-date on this subject since many of these “expert” tech writers are not forward thinking data scientists themselves. Best case scenario, they have spend a few minutes on the web, probably focusing on the results on the first page of a search engine for the bulk of their material. And shocking as it may be, this material may be geared more towards what’s more popular rather on what’s more accurate. Alternatively, they may have relied on what some data science guru once said on the topic, information that may no longer be particularly relevant.  Apart from that, the writers who delve into the production of this sort of articles (or infographics in some cases) have their own biases. Probably they took a programming course at university so if a particular programming platform comes up on their “research” they may be more likely to highlight it. After all, this would make them knowledgeable since they have hands-on experience on that platform, even if it’s not that useful to data science any more.  What’s more, many people who write about these topics don’t want to take risks with newer things. It’s much safer to mention languages that everyone knows about and which have a large community around them, than mention newer ones that may be despised by the hardcore users of older coding platforms. 

Hope for the Future
For better or for worse, an article on the social media has a limited life span. After all, its purpose is mainly to get enough people to click on a particular link where a given site serves ads, so that the people owning the site can get some revenue from said ads. Therefore, if the article is forgotten in a week, its producers won’t lose any sleep over it.  Books and subscription-based videos are not like that though. Neither are technical conferences. So, since the new trends are geared more towards this kind of platforms to become well-known, they are not that much hindered by social media misinformation. After all, if a programming language is good, this is something that will eventually show, even if the fan-boys of the more traditional languages would sooner die than change their views on their favorite coding platforms. 

What You Can Do
So, instead of getting swayed by this or the other “expert” with X thousand followers (many of whom are probably either bots or bought followers), you can do your own research. Check out what books are out there on the various programming languages and if they hint towards applicability in data science. Check out videos on Safari and other serious educational platforms. Look at what new language conferences are out there and how they cover data science related topics. And most importantly, try some of these languages yourself. This way you’ll have some more reliable data when making a decision on what language is most relevant and most future-proof in our field, rather than blindly believe whatever this or the other “expert” on the social media says.