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Sentiment Analysis by Fusing Text and Location Features of Geo-tagged Tweets
2020
IEEE Access
Twitter sentiment analysis provides valuable feedback from public emotion concerning certain events or products. Current research has been focused on obtaining sentiment features from vectorized lexical and syntactic feature from tweets, without further context. In this paper, we demonstrated how vectorized location information could be combined with word embeddings to produce a hybrid representation, which has resulted in an improvement on a tweet sentiment classification task. The location
doi:10.1109/access.2020.3027845
fatcat:wdd2mzup2zbevjxuo4o6ckq3kq