Recognizing the vocabulary of Brazilian popular newspapers with a free-access computational dictionary
This work addresses the problem of incomplete lexical resources for analyzing Brazilian popular media, which is incremental as it assesses and suggests improvements to existing dictionaries.
The study evaluated the coverage of two free-access computational dictionaries for Brazilian Portuguese on vocabulary from popular newspapers, finding that 19% of word types in one newspaper and 13% in another were not recognized, with minimal improvement between dictionary versions.
We report an experiment to check the identification of a set of words in popular written Portuguese with two versions of a computational dictionary of Brazilian Portuguese, DELAF PB 2004 and DELAF PB 2015. This dictionary is freely available for use in linguistic analyses of Brazilian Portuguese and other researches, which justifies critical study. The vocabulary comes from the PorPopular corpus, made of popular newspapers Di{á}rio Ga{ú}cho (DG) and Massa! (MA). From DG, we retained a set of texts with 984.465 words (tokens), published in 2008, with the spelling used before the Portuguese Language Orthographic Agreement adopted in 2009. From MA, we examined papers of 2012, 2014 e 2015, with 215.776 words (tokens), all with the new spelling. The checking involved: a) generating lists of words (types) occurring in DG and MA; b) comparing them with the entry lists of both versions of DELAF PB; c) assessing the coverage of this vocabulary; d) proposing ways of incorporating the items not covered. The results of the work show that an average of 19% of the types in DG were not found in DELAF PB 2004 or 2015. In MA, this average is 13%. Switching versions of the dictionary affected slightly the performance in recognizing the words.