Polarity lexicons are lists of words (or meanings) where each entry is labelled as positive, negative or neutral. These lists are not available for different languages and specific domains. This work proposes and evaluates a new algorithm to classify words as positive, negative or neutral, relying on a small seed set of words, a common dictionary and a propagation algorithm. We evaluate the positive and negative polarity propagation of words, as well as the neutral polarity. The propagation is evaluated with different settings and lexical resources.
|Title of host publication||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Publication status||Published - 1 Jan 2012|
|Event||PROPOR - Computational Processing of the Portuguese Language - |
Duration: 1 Jan 2012 → …
|Conference||PROPOR - Computational Processing of the Portuguese Language|
|Period||1/01/12 → …|
Cavalheiro Marques, N. M. (2012). A Bootstrapping Algorithm for Learning the Polarity of Words. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 229-234) https://doi.org/10.1007/978-3-642-28885-2_26