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 → …

Keywords

    Cite this

    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
    Cavalheiro Marques, Nuno Miguel. / A Bootstrapping Algorithm for Learning the Polarity of Words. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012. pp. 229-234
    @inproceedings{dbfb99459c8a4b0cb86c9dadf6faa8c6,
    title = "A Bootstrapping Algorithm for Learning the Polarity of Words",
    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.",
    keywords = "polarity lexicon, opinion mining, sentiment analysis, lexicon expansion, polarity of words",
    author = "{Cavalheiro Marques}, {Nuno Miguel}",
    year = "2012",
    month = "1",
    day = "1",
    doi = "10.1007/978-3-642-28885-2_26",
    language = "Unknown",
    isbn = "978-3-642-28884-5",
    pages = "229--234",
    booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

    }

    Cavalheiro Marques, NM 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, PROPOR - Computational Processing of the Portuguese Language, 1/01/12. https://doi.org/10.1007/978-3-642-28885-2_26

    A Bootstrapping Algorithm for Learning the Polarity of Words. / Cavalheiro Marques, Nuno Miguel.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012. p. 229-234.

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

    TY - GEN

    T1 - A Bootstrapping Algorithm for Learning the Polarity of Words

    AU - Cavalheiro Marques, Nuno Miguel

    PY - 2012/1/1

    Y1 - 2012/1/1

    N2 - 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.

    AB - 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.

    KW - polarity lexicon

    KW - opinion mining

    KW - sentiment analysis

    KW - lexicon expansion

    KW - polarity of words

    U2 - 10.1007/978-3-642-28885-2_26

    DO - 10.1007/978-3-642-28885-2_26

    M3 - Conference contribution

    SN - 978-3-642-28884-5

    SP - 229

    EP - 234

    BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    ER -

    Cavalheiro Marques NM. 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). 2012. p. 229-234 https://doi.org/10.1007/978-3-642-28885-2_26