Open AccessSocial Network Mental Disorders Detection via Online Social Media Mining
Author(s) -
Narinder Kaur and Lakshay Monga
Publication year - 2021
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst0701006
Subject(s) - sentiment analysis , social media , python (programming language) , computer science , data science , social network (sociolinguistics) , order (exchange) , information retrieval , world wide web , data mining , artificial intelligence , finance , economics , operating system
Social Network Mental Disorder Detection” or “SNMD” is an approach to analyse data and retrieve sentimentthat it embodies. Twitter SNMD analysis is an application of sentiment analysis on data from Twitter(tweets), in order to extract sentiments conveyed by the user. In this paper, we aim to review some papersregarding research in sentiment analysis on Twitter, describing the methodologies adopted and modelsapplied, along with describing a generalized Python based approach. A prototype system is developed andtested.