Abstract: In this paper, we report a qualitative and quantitative evaluation of a hand-crafted set of discourse features and their interaction with
different text types. To be more specific, we compared two distinct text
types --- scientific abstracts and their accompanying full texts --- in terms
of linguistic properties, which include, among others, sentence length,
coreference information, noun density, self-mentions, noun phrase count,
and noun phrase complexity. Our findings suggest that abstracts and
full texts differ in three mechanisms which are size and purpose bound.
In abstracts, nouns tend to be more densely distributed, which indicates
that there is a smaller distance between noun occurrences to be observed
because of the compact size of abstracts. Furthermore, in abstracts we
find a higher frequency of personal and possessive pronouns which au-
thors use to make references to themselves. In contrast, in full texts we
observe a higher frequency of noun phrases. These findings are our first
attempt to identify text type motivated linguistic features that can help
us draw clearer text type boundaries. These features could be used as pa-
rameters during the construction of systems for writing evaluation that
could assist writing tutors in text analysis, or as guides in linguistically-
controllable neural text generation systems.