作者: Amna Dridi , Diego Reforgiato Recupero
DOI: 10.1007/S13042-017-0727-Z
关键词: Semantics 、 Microblogging 、 Artificial intelligence 、 Written language 、 Affect (linguistics) 、 Computer science 、 Social media 、 Field (computer science) 、 Sentiment analysis 、 Natural language processing 、 Frame semantics
摘要: … First, we aim to evaluate whether our training data with labels derived from frame semantics and lexical resource BabelNet is useful for training sentiment classifiers for social media. …