Latent semantic analysis for tagging activation states and identifiability in northwestern Mexican news outlets

The present work aims to study the relationship between measures, obtained from Latent Semantic Analysis (LSA) and a variant known as SPAN, and activation and identifiability states (Informative States) of referents in noun phrases present in journalistic notes from Northwestern Mexican news outlets written in Spanish. The aim and challenge is to find a strategy to achieve labelling of new / given information in the discourse rooted in a theoretically linguistic stance. The new / given distinction can be defined from different perspectives in which it varies what linguistic forms are taken into account. Thus, the focus in this work is to work with full referential devices (n = 2 388). Pearson's R correlation tests, analysis of variance, graphical exploration of the clustering of labels, and a classification experiment with random forests are performed. For the experiment, two groups were used: noun phrases labeled with all 10 tags of informative states and a binary labelling, as well as the use of two bags-of-words for each noun phrase: the interior and the exterior. It was found that using LSA in conjunction with the inner bag of words can be used to classify certain informational states. This same measure showed good results for the binary division, detecting which sentences introduce new referents in discourse. In previous work using a similar method in noun phrases in English, 80% accuracy (n = 478) was reached in their classification exercise. Our best test for Spanish reached 79%. No work on Spanish using this method has been done before and this kind of experiment is important because Spanish exhibits a more complex inflectional morphology.