Open AccessAlgorithm for Emotion Prediction using Twitter Dataset
Author(s) -
K. Arulmozhi,
R. Ponnusamy
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d5277.118419
Subject(s) - bigram , social media , computer science , anger , happiness , sentiment analysis , artificial intelligence , enhanced data rates for gsm evolution , emotion recognition , sadness , machine learning , emotion classification , psychology , world wide web , social psychology , trigram
In today's internet world almost each and everyone uses Smartphone and they are all also active in various social media. In general social media contains a huge amount of data that can be extracted and utilized to find various data insights including polarity emotion etc... This research paper mainly investigates in emotion predection using a machine learning approach . Here a novel algorithm was introduced to predict the emotion of tweets . The algorithm mainly deals with emotion Prediction by utilizing various parameters like unigram , bigram , edge weight matrix , frequency matrix and so on . Finally , the result was predicted with the emotions of the tweets . While testing with various search terms this algorithm performs well in Predicting the emotion like anger, happiness and so on .