Applying word space models to sociolinguistics 119by a more quantitative approach. For instance, if we want to find out
whether the use of words like Islam in newspapers has really changed after
9/11, we cannot satisfy ourselves with focusing on the handful of articles
that a manual analysis is necessarily restricted to. In order to uncover the
larger trends or differences in habit, some of which may even happen sub-
consciously, we need to make use of a more advanced linguistic apparatus.
This can be done by studying the words that are used together with Islam.
As Dunn, Moore and Nosek (2005) point out, these context words can dra-
matically change people’s perception of the incident that is being de-
scribed. Even subtle differences like substituting strategy for plot can con-
tribute to people’s opinion of an action, as either terrorist or patriotic. We
believe that the framework of distributional semantics can help us identify
such underlying changes and trends. Because word space models can neatly
deal (and indeed, only work well) with large quantities of data, they allow a
detailed linguistic investigation of word use in large corpora.- Case study
3.1. Experimental setupAs we indicated above, we will use two types of word space models for our
analyses. The document-based model will mainly give us information on
the syntagmatic relations of our target words. These often capture the gen-
eral topic of the articles that the target words appear in. The syntax-based
model will give us more paradigmatically related words. These are words
that often have the same syntactic function or role as the target word. In
total, we take eight types of syntactic relations into account:
- subject of verb v (su/v),
- direct object of verb v (obj1/v) ,
- prepositional complement to verb v introduced by preposition p
(pc/v_p), - head of an adverbial PP to verb v introduced by preposition p
(advPP/v_p), - modified by adjective a (mod/a),