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This paper describes a system attended in the SemEval-2018 Task 1 "Affect in tweets" that predicts emotional intensities. We use Group LSTM with an attention model and transfer learning with sentiment classification data as a source data (SemEval 2017 Task 4a). A transfer model structure consists of a source domain and a target domain. Additionally, we try a new dropout that is applied to LSTMs in the Group LSTM. Our system ranked 8th at the subtask 1a (emotion intensity regression). We alsodoi:10.18653/v1/s18-1044 dblp:conf/semeval/KimL18 fatcat:zwtisih65ra3vd5664nzirtxw4