Emotion Mining Mechanism over Texts in Social Media
Luis Casillas, Alejandro Ramirez · Research in Computing Science · 2019
Nowadays societies are clearly bound to social networking through the Internet.It is common to find out people posting remarks, quotes or moods in social media.Leaders, politicians, celebrities, and ordinary people have posted on social media as a regular in their expression range.Even organizations generate postings on social networks.Humans' manifestation is always linked to the emotions they have.Authors believe that it is possible to discover the sentiment expression from texting.This proposal consists of a model to gather, classify, and emotionally-assess the texting in social networks.The model collects text posts from social media, processes the postings, and generates an emotional assessment.Such evaluation could be bound to the mood of postings' authors.The emotional-assessment consist of inference mechanisms based on knowledge coming from affective dictionaries and automated reasoning.