{
    "o:id": 14991,
    "url": "https://chloe.cnr.it/s/BiDiAr/item/14991",
    "o:resource_template": "Academic Article",
    "o:resource_class": "bibo:AcademicArticle",
    "dcterms:title": [
        "A new ANEW: Evaluation of a word list for sentiment analysis in microblogs"
    ],
    "dcterms:creator": [
        "Nielsen, Finn Årup"
    ],
    "dcterms:date": [
        "2011"
    ],
    "dcterms:abstract": [
        "Sentiment analysis of microblogs such as Twitter has recently gained a fair amount of attention. One of the simplest sentiment analysis approaches compares the words of a posting against a labeled word list, where each word has been scored for valence, -- a 'sentiment lexicon' or 'affective word lists'. There exist several affective word lists, e.g., ANEW (Affective Norms for English Words) developed before the advent of microblogging and sentiment analysis. I wanted to examine how well ANEW and other word lists performs for the detection of sentiment strength in microblog posts in comparison with a new word list specifically constructed for microblogs. I used manually labeled postings from Twitter scored for sentiment. Using a simple word matching I show that the new word list may perform better than ANEW, though not as good as the more elaborate approach found in SentiStrength."
    ],
    "dcterms:isPartOf": [
        "arXiv"
    ],
    "bibo:citedBy": [
        "13604"
    ],
    "bibo:doi": [
        "https://doi.org/10.48550/arXiv.1103.2903"
    ],
    "bibo:volume": [
        "1103.2903"
    ],
    "foaf:homepage": [
        "https://www.zotero.org/groups/5293298/bidiar/items/DCAEK3HD/item-list"
    ]
},