Searching for the tag Julia in a standard search interface is not very useful. After thinking hard for 3 minutes, I guess JuliaLang is the obvious best tag, in part because it is already in use.
The motivation for the question is linkedin “skills”. (I’m not interested in debating here the value of this feature in linkedin) I use this example, but the issue is more general. Searching for Julia Lang on linkedin yields 1K+ results mostly about people with that name. Searching for Julia language seems to add a few needles to an enlarged haystack. Presumably if one pays the recruiter’s fee, filtering on “skills” is possible. But, for ordinary users it is not.
Searching linkedin for python returns two million hits, most of which likely refer to the language. Searching for JuliaLang returns 68 hits. These do seem to refer to the language. But, I have no way of finding profiles that refer to the language as Julia
It seems to me that promoting a single tag would be helpful.
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How does R do it? It seems “julialang” might be best?
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I tried a few searches (on linkedin). It’s difficult to measure because python is more widespread than R, which is more widespread than Julia. (still R is quite popular).
Percent of hits with R that refer to the language seems to be about 5 to 20. R+D is more common.
Rlang get no hits (AFAICT) referring to the language. Search engine suggests erlang.
“R language” does quite a bit better. Most hits are for the language. But, a significant minority are not.
“Julia language” does far better than anything in my initial post. A substantial minority of the first few pages refer to the language.
python returns, as I already mentioned, 2 million hits. I looked for a few minutes and was unable to find one that does not refer to the language.
For Julia and R, I suppose it’s debatable whether there is a problem. I think the argument for “yes, there is a problem” is strong. For python, there is clearly no problem. The problem would exist for someone who wanted to refer to the snake.
It is likely possible to do better with Boolean searches, etc.
I still think JuliaLang, especially as a tag, is useful. This is as unambiguous as python, and obviates the need to think about how to search.
Yes, julialang is a good choice.
And it agrees with the (case-insensitive) twitter hashtag.
My $0.02: hoping people will write ‘julialang’ on LinkedIn seems like a lost cause. It’s not what job descriptions or recruiters will likely type, because no hiring manager is going to say “I’m looking for someone with julialang experience”
Maybe you misunderstand my point. I’m talking about search algorithms and database queries. “I’m looking for…” is meant to be read by a human.
Today, a hiring manager, or whoever is responsible for carrying out the search, will find (sooner or later) that julialang is in fact one of the best queries (on linkedin) for finding someone with Julia skills. She will get several hits and no false positives. She will also miss a lot of profiles that use the tag Julia in the skills section. “julia language” (maybe with quotes, depends on the search interface) will probably get some others. (There is in fact a natural language teaching outfit named Julia that has a presence on linkedin.)
If she is looking for profiles that mention the python language, python will get more or less all of and only the desired profiles. The question of choosing a query for these profiles will not reach the level of conscious thought.
If every recruiter and every Julia programmer knew that julialang is the standard tag/keyword for Julia (not in natural language), this would approximate the python situation. Let me put it another way, suppose for the past year, julialang.org, and juliacomputing.com had had some prominent notice saying, Julia programmers! Want to get noticed by recruiters ? Use julialang in social media tags and lists of keywords. I guess that the number of positive hits one would find today on linkedin would be higher. This would be a great advantage for promoting Julia. What are the disadvantages ?
Of course, as Julia becomes more popular, it will become easier to search for it, but the problem won’t disappear.