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In a real world, emotion plays a significant role in rational actions in human communication. Given the potential and importance of emotions, in recent years, there has been growing interest in the study of emotions to improve the capabilities of current human-robot interaction. The emotion recognition from text modality is a necessary step to develop affective conversational interfaces. In this paper, we present an effective hybrid approach to improve the performance of emotion recognition from text by combining linguistic, pragmatic, and keyword spotting features.