Article Instance

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{
    "pk": 25756,
    "title": "Multiple Language Gender Identification for Blog Posts",
    "subtitle": null,
    "abstract": "In data-driven gender identification, it has been so far largely\nassumed that the same types of (mostly content-oriented) data\nfeatures can be used to differentiate between male and female\nauthors. In most cases, this distinction is done in a monolingual\nscenario. In this work, we discuss a set of features that\ndistinguish between genders in six different datasets of blog\ndata in English, Spanish, French, German, Italian and Catalan\nwith accuracies that range from 77% to 88%. Using a reduced\nset of language-independent structural features in a multilingual\nscenario we first identify the gender and then the gender\nand language of the author, achieving accuracies higher than\n74%.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Natural Language Processing; Text Categorization;\nAuthor Profiling; Gender Identification"
        }
    ],
    "section": "Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/66d4z61k",
    "frozenauthors": [
        {
            "first_name": "Juan",
            "middle_name": "",
            "last_name": "Soler-Company",
            "name_suffix": "",
            "institution": "Pompeu Fabra University",
            "department": ""
        },
        {
            "first_name": "Leo",
            "middle_name": "",
            "last_name": "Wanner",
            "name_suffix": "",
            "institution": "Pompeu Fabra University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2015-01-01T13:00:00-05:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/25756/galley/15380/download/"
        }
    ]
}