Open AccessAnalysis of sentiment in twitter using logistic regression
Author(s) -
R. Lakshmi,
Satya R. B. Divya,
R. Valarmathi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.33.14849
Subject(s) - sentiment analysis , logistic regression , social media , support vector machine , computer science , artificial intelligence , machine learning , world wide web
Social Platforms such as Twitter, Facebook are not always the good places and when explored there exists a dark side to it. The main objective of this research is to identify the sentiment of a tweet in twitter and also further analyse a twitter accounts activity. Logistic regression and text blob are used to identify the sentiment of the tweets, as for the taken datasets they provided the highest accuracy when compared with other algorithms such as GaussianNB, BernoulliNB, SVM. The datasets are extracted from twitter and split into training and testing data using which the model is trained to classify the sentiments of a tweet and then the analysis of a twitter account is done.