Part of the problem is that the physicists seem to have not understood the dataset they were working with and were in any case confused about what a word is, which is a problem if you are studying words! Influential linguist Mark Liberman wrote "The paper's quantitative results clearly will not hold for anything that a linguist, lexicographer, or psychologist would want to call 'words.'"
Zimmer concludes that
Tensions over [the paper] may really boil down to something simple: The need for better communication between disciplines that previously had little to do with each other. As new data models allow mathematicians and physicists to make their own contributions about language, scientific journals need to make sure that their work is on a firm footing by involving linguists in the review process. That way, culturomics can benefit from an older kind of scholarship -- namely, what linguists already know about humans shape words and words shape humans.Beyond pointing out that linguists and other non-physicists don't already apply sophisticated mathematical models to language -- there are several entire fields that already do this work, such as computational linguistics and natural language processing -- I respectfully suggest that involving linguists at the review process is way too late. If the goal is to improve the quality of the science, bringing in linguists to point out that a project is wrong-headed after the project is already completed doesn't really do anyone much good. I guess it's good not to publish something that is wrong, but it would be even better to publish something that is right. For that, you need to make sure you are doing the right project to begin with.
This brings me to the difficulty with interdisciplinary research. The typical newly-minted professor -- that is, someone just starting to do research on his/her own without regular guidance from a mentor/advisor -- has studied that field for several years as an undergraduate, 5+ years as a graduate student, and several more years as a post-doc. In fact, in some fields even newly-minted professors aren't considered ready to release into the wild and are still working with a mentor. What this tells me is that it takes as much as 10 years of training and guidance before you are ready to be fully on your own. (This will vary somewhat across disciplines.)
Now maybe someone who has already mastered one scientific field can master the second one more quickly. I'm frankly not sure that's true, but it is an empirical question. But it seems very unlikely that anyone, no matter how smart nor how well trained in their first field, is ready to tackle big questions in a new field without at least a few years of training and guidance from an experienced researcher in that field.
This is not a happy conclusion. I'm getting a taste of this now, as I cross-train in computational modeling (my background is pure experimental). It is not fun to go from being regarded as an expert in your field to suddenly being the least knowledgeable person in your laboratory. (After a year of training, it's possible I'm finally a more competent computational modeler than at least the incoming graduate students, though it's a tough call -- they, at least, typically have several years of relevant undergraduate coursework.) And I'm not even moving disciplines, just sub-disciplines within cognitive science!
So it's not surprising that some choose the "shortcut" of reading a few papers, diving in, and hoping for the best, especially since the demands of the career mean that nobody really has time to take a few years off to learn a new discipline. But it's not clear that this is a particularly effective strategy. All the best interdisciplinary work I have seen -- or been involved in -- involved an interdisciplinary team of researchers. This makes sense. It's hard enough to be an expert in one field. Why try to be an expert in two fields when you could just collaborate with someone who has already done the hard work of becoming an expert in that discipline? Just sayin'.