How to improve the quality and visibility of research?
How to improve the quality and visibility of research?


I think this is a very relevant question, but also a very broad one. Clearly there is no simple answer, so I will try to give a few general directions. Also I think it makes sense to distinguish between the field-specific aspects and the more general aspects across academic fields.

Reproducibility in Natural Language Processing (NLP)

I happen to work in this field as well and I can relate to the problems described by OP. The field has a quite serious problem with reproducibility: this is mostly due to NLP being a very experimental domain, where experiments often involve a lot of complex parameters and where data is extremely diverse by nature. Additionally there's no strong incentive for strict reproducibility protocols in NLP, as opposed to other domains where mistakes are not an option (e.g. health or security).

Still, the community is aware of the issue and has been trying to address it for some time:


There's now a well established tradition of "shared tasks", scientific competitions meant to (1) provide benchmark datasets and (2) compare different approaches in a uniform way.
While still not the general rule, it's becoming the norm to not only publish a paper but also the code and/or data used for the experiment. Conferences have been encouraging this for a few years now by allowing the submission of supplementary material.
Through various other initiatives: proposing a specific category for reproducibility papers, building a repository of language resources, etc.


Of course technical results ("new model X improves performance by Y%") are the bread and butter of conferences, but my impression is that the best papers acknowledged by the community (e.g. best papers awards at conferences) are rarely pure technical papers, original ideas and insights tend to be valued more (but this might be a subjective perception based on my limited experience).

Visibility and academic reputation


  blog posts, how-to guides, stack overflow answers, discussion group records, are all of zero academic merit. 


This is not completely true, because:


Building a reputation through various means can help your research get cited
Outreach and communication towards non-academic publics is increasingly encouraged (see for instance the growing trend of citizen science projects)


However it's true that these activities (unless very successful) are usually less valued than the good old publication record. Unfortunately at many levels research and researchers are evaluated against simplified indicator (publications, citations, h-index...), despite the obvious biases in this. Note that most researchers are aware that publications are not necessarily synonymous for research quality, but funding bodies are happy to use this kind of performance indicators. 

My personal publication strategy is along the following lines:


Target top conferences/journals for any (potentially) significant contribution. 
Target reputable specialized workshops or small conferences for prospective ideas, work in progress and other kinds of moderately significant contributions. It adds a modest line to my publication record, but more importantly this way I can meet and see what the community is doing on a specific topic.


Caution: I don't have a particularly successful academic career myself, so don't assume that my advice is good ;)