Borrowing the geometry-flavored term vector for the representation of a data point constituting a multidimensional magnitude+direction value[1] as opposed to the term explanatory variable from linear algebra/statistics is just happenstance, and is not an invention of a new term (or even a case of applying an existing term to something new).
Feature vectors and explanatory variables are, quite simply, two labels for the very same thing[2][3], and are often used interchangeably depending on context.
As for the familiarity argument, thinking of the data points as vectors is actually quite useful as a framing device for problem statements in terms of the tools and solutions it suggests[4].
[1] https://en.wikipedia.org/wiki/Feature_vector
[2] https://en.wikipedia.org/wiki/Vector_space
[3] https://en.wikipedia.org/wiki/Dependent_and_independent_vari...
[4] https://www.technologyreview.com/s/602025/how-vector-space-m...
Their example “A woman needs a man like a fish needs a bicycle.” is not sarcastic so much as colorful analogy.
The researcher's word2vec approach is really a search for 'non-sequitur' -- any sentence that semantically goes of the rails at the end, it's probably better at detecting humor in general than 'sarcasm'