The Road to Emotion Mining in Social Network

Abstract

Affective computing is a highly computer research trend in last years, which related to human emotions and how computer interacts. While emotion is a fundamental in human experience, it becomes an ideal resource for servicing business or decision making. In ancient times, natural interfaces are likely to be used to provide ubiquitous computing. Although great achievement done, there still exist three challenges which are Cheap, Low power and software system. With the explosive growth of social media, people are using it to express their emotion or opinion. Currently, there are large amount of user generated data in different format ( i.e. Blog, Tweets, Posts, discussion forums) that represent individual expression feelings towards daily life activates whether it is product, topic, event, news, or personal life. As a result, a lot of researchers are done for detecting what humans feel now in social network; they fall under the scope of topic called emotion mining, opinion mining, or sentiment analysis. In this paper, we will survey the development done for emotion mining with a comparative study for different approaches. In addition, an investigation for technology used in this area and how it is applied, will be presented.

Sentiment Analysis: Comparative Study between GSVM and KNN

“…Different approaches in sentiment classification area are presented in (Mohamed and Ezzat, 2015;Shivhare and Khethawat, 2012;Kalaivani and Shunmuganathan, 2014;Guo et al, 2003), which is categorized based on lexical analysis or Machine Learning (ML) techniques.…”