Abstract
This paper presents an emotion mining system, which assigns emoticons to newspaper articles into a pre-defined emotion category based on the underlying emotion in the news. Next, the system makes recommendation to the reader by tagging the news headline with the respective emoticons. Users are then able to decide whether to read the news based on the emoticons provided. The system also provides a filter for the users to choose the category of news to read following the emoticons.
Cite
CITATION STYLE
Kasinathan, V., Mustapha, A., Yong, L. Z., & Aida Zamnah, Z. A. (2017). Emotional Mining: Tagging Emoticons to Online News. In IOP Conference Series: Materials Science and Engineering (Vol. 226). Institute of Physics Publishing. https://doi.org/10.1088/1757-899X/226/1/012079
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