A Bootstrapping Algorithm for Learning the Polarity of Words

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

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.
Original languageUnknown
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages229-234
ISBN (Electronic)978-3-642-28885-2
DOIs
Publication statusPublished - 1 Jan 2012
EventPROPOR - Computational Processing of the Portuguese Language -
Duration: 1 Jan 2012 → …

Conference

ConferencePROPOR - Computational Processing of the Portuguese Language
Period1/01/12 → …

Cite this