Text Preprocessing on Emotional Tweets Case Study: Covid-19 Vaccine Rejection

Dewi Melisa Putri, Yulian Findawati
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Abstract

Emotion is a feeling, response, reaction to an event or event experienced by a person, can be expressed verbally (spoken) or non-verbally (body language). In the digital world, more precisely text-based social media, humans express their emotions by giving opinions through text / typing and there is a need for emotional analysis related to what opinions are conveyed by that person. Therefore, to overcome the above problems, it is necessary to classify to find out what type of emotion is conveyed in the text. Emotion classification is a technique to extract information in the form of a person's response or opinion on an issue or event which is then grouped based on the types of emotions. The opinions used will be taken from social media twitter. The types of emotion grouping are divided into seven classes, namely anticipation, pleasure, trust, anger, disgust, fear, and sadness. In this practical work, the author has created a dictionary that contains key words for each aspect of emotion
情感推文文本预处理案例研究:Covid-19 疫苗拒收
情绪是一个人对某一事件或经历的事件的感觉、反应、回应,可以用语言(口头)或非语言(肢体语言)表达。在数字世界中,更确切地说,在基于文本的社交媒体中,人类通过文本/打字发表意见来表达情感,因此需要对该人所表达的意见进行情感分析。因此,为了解决上述问题,有必要对文本进行分类,以找出文本中传达的情感类型。情感分类是一种提取信息的技术,其形式是一个人对某一问题或事件的反应或意见,然后根据情感类型对其进行分组。所使用的观点将来自社交媒体 twitter。情绪分组类型分为七类,即期待、愉悦、信任、愤怒、厌恶、恐惧和悲伤。在这项实践工作中,作者创建了一个词典,其中包含情绪各方面的关键词
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