用于情感分析的WhatsApp聊天预处理和表情符号分类

2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2020-10-07 DOI:10.1109/I-SMAC49090.2020.9243443

Astha Mohta, Atishay Jain, Aditi Saluja, S. Dahiya

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引用次数: 6

摘要

WhatsApp是广受欢迎的社交媒体服务之一，拥有超过20亿注册用户。WhatsApp是人们生活中不可或缺的沟通媒介。他们用WhatsApp通过短信分享自己的感受。WhatsApp在180多个国家都有业务，代码转换很常见。与此同时，随着表情符号的使用和普及，表情符号在情感分析中变得不可或缺。在本文中，我们讨论了将非结构化WhatsApp消息转换为结构化形式的方法，在这种方法上可以执行各种用于情感分析的数据挖掘技术。我们处理代码混合、不同表情符号及其所描述的情绪的方法，最后讨论了使用该算法进行基本分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Pre-Processing and Emoji Classification of WhatsApp Chats for Sentiment Analysis

WhatsApp is among the popular social media service with over 2 billion registered users. WhatsApp is integral in people's life as a medium of communication. They use WhatsApp to share their feelings through text messages. With WhatsApp present in over 180 countries, code-switching is common. Along with this, with the increase in usage and prevalence of emojis, emojis have become indispensable during sentiment analysis. Throughout this paper, our approach to convert unstructured WhatsApp messages to a structured form is discussed on which various data mining techniques for sentiment analysis can be performed. Our approach to deal with code-mixing, different emojis and the emotions they depict, and finally, perform basic analysis using this algorithm is discussed.

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来源期刊

2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

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