文章基本信息

标题：Emotion Prediction using Machine Learning Techniques
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作者：Areeba Shamsi ; Sabika Nasir ; Mishaal Amin Hajiani 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2019
卷号：19
期号：6
页码：166-172
出版社：International Journal of Computer Science and Network Security
摘要：Sentiment analysis is the field of study that analyzes people's opinions, sentiments, evaluations, and emotions from written language or their voice. Nowadays, an increasing number of online users has led to the growing influence of human emotions on the online community. Understanding the opinions behind user-generated content automatically is of great help for commercial and political use, among others. This assignment can be conducted on different levels by classifying the polarity of words, sentences or entire documents. Various emotions are conveyed on social media, it helps to identify the mood of a user with which the review was written. This project focuses on the implementation of unsupervised learning by applying different types of clustering techniques such as k-means and fuzzy c-means on a data describing human emotions. The emotions in the content are clustered with basic emotions such as fear, sad, happy etc. Emotional analysis can be used for efficient recommendation process.
关键词：Recommendation process; sentimental analysis; unsupervised learning; user generated content; K-means; fuzzy c-means.