An Approach to Disambiguate the Innate Sense of a Message with the Help of Emoji

Saikat Bhattacharyya, Surela Maity, Suraj Maiti, A. R. Pal, Antara Pal
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Abstract

This project aims to understand the tonality of a text using emoticons as the predictor. The emoticons have transpired to be an increasingly significant and standardized part of modern textual inputs. The combination of visual and textual content in the same message builds a compact form of communication, sometimes which becomes tough to portray by the words only. Emoticon prediction and word-emoticon embedding could be used for any kind of Sentiment Analysis based works like Opinion Mining, User Profiling etc. This work focuses on identifying the tone of emotion behind a body of text which is used to analyze the sentiment of a user according to h(is)er comments or messages in online media. This experiment is carried out on the comments collected from some Twitter handles, Facebook walls and Whatsapp conversations. During the experiment, it is observed that in a few cases the senses of different comments are not possible to retrieve only from the words, but the texts which are combined with some emoticons are evaluated correctly. Challenges faced in this work are explained at the end of this report.
一种利用表情符号消除信息固有意义歧义的方法
这个项目旨在使用表情符号作为预测器来理解文本的调性。表情符号已经成为现代文本输入中越来越重要和标准化的一部分。在同一信息中,视觉和文本内容的结合构建了一种紧凑的交流形式,有时仅靠文字很难描绘出来。表情符号预测和单词表情符号嵌入可以用于任何基于情感分析的工作,如意见挖掘,用户分析等。这项工作的重点是识别文本正文背后的情绪基调,根据在线媒体上的评论或消息来分析用户的情绪。这个实验是在从一些Twitter的处理,Facebook的墙和Whatsapp的对话中收集的评论上进行的。在实验过程中,我们观察到,在少数情况下,不同评论的意义不可能仅从单词中检索,但结合一些表情符号的文本是正确的评估。本报告的最后解释了这项工作面临的挑战。
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