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A Method to Identify the Current Mood of Social Media Users

机译：一种识别社交媒体用户当前情绪的方法

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摘要

Mood of a person changes frequently during a day. A mood can be categorized as happy, sad, calm and angry. Most of the people today share their daily activities, opinions, feelings regularly in social media. Identification of current mood will be useful for recommendation systems to change or elevate moods. Thus, this proposed system identifies the current mood of a person by mining their social media contents such as posts, comments, image posts and emoticons. In the proposed solution, a score for the current mood is calculated in two stages; a score for text contents (images with text and posts/comments) and score for emoticons were computed. Posts made within a 24-hour period will be considered for the current mood and scores for multiple posts are combined using a temporal weighted average. Text classification is done using a 1D Convolution Neural Network and emoticon classification is performed using a survey. Finally, an overall accuracy of 85% is achieved.
机译：一个人的情绪在一天中经常变化。心情可以归类为快乐，悲伤，平静和生气。大多数人今天分享他们的日常活动，意见，定期在社交媒体中。确定当前情绪的识别对于建议制度将改变或提高情绪。因此，这一提出的系统通过挖掘其社交媒体内容，例如帖子，评论，图像帖子和表情符号来识别人的当前情绪。在提出的解决方案中，在两个阶段计算目前情绪的分数;计算文本内容（具有文本和帖子/评论的图像）和表情符号的分数。在24小时内完成的帖子将考虑当前的情绪和多个帖子的分数使用时间加权平均值相结合。文本分类是使用1D卷积神经网络完成的，使用调查执行表情符号分类。最后，实现了85％的整体准确性。

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