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Real-time Emotion Classification of Tweets

机译:推特的实时情感分类

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摘要

Despite adding emotions to applications has proven to enhance the user experience, emotion recognition applications are still not widely available nor used. Within this paper, emotion recognition is done on Twitter tweets using six emotion classification algorithms that are compared on precision and timing. The paper shows that precision can be enhanced by 5.02% compared to the current state-of-the-art by improving the features. Furthermore, the presented algorithms work in realtime.
机译:尽管对应用程序的情感已被证明增强了用户体验,但情感识别应用仍然没有广泛可用。在本文中,使用六种情感分类算法在Twitter推文中完成了情感识别,这些算法在精度和时序上进行了比较。本文通过改善特征,与当前最先进的精度可以增强5.02%。此外,所呈现的算法实时工作。

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