Mining Twitter Data for Depression Detection

Health care twitter analysis deals with the health related tweets through sentimental analysis by the patients themselves. The application of sentiment analysis has grown enormously. Its application in health care has great potential to analyze and improve the health of a country. In this paper, we...

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Published inInternational Conference on Signal Processing and Communication (Online) pp. 186 - 189
Main Authors Arora, Priyanka, Arora, Parul
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2019
Subjects
Depression
Dictionaries
Diseases
Feature extraction
natural language processing
Sentiment analysis
Support vector machines
Twitter
Online AccessGet full text
ISBN9781538694350
1538694352
ISSN2643-444X
DOI10.1109/ICSC45622.2019.8938353

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Abstract Health care twitter analysis deals with the health related tweets through sentimental analysis by the patients themselves. The application of sentiment analysis has grown enormously. Its application in health care has great potential to analyze and improve the health of a country. In this paper, we try to analyze health tweets for Depression, Anxiety from the mixed tweets by using Multinomial Naive Bayes and Support Vector Regression (SVR) Algorithm as a classifier.
AbstractList Health care twitter analysis deals with the health related tweets through sentimental analysis by the patients themselves. The application of sentiment analysis has grown enormously. Its application in health care has great potential to analyze and improve the health of a country. In this paper, we try to analyze health tweets for Depression, Anxiety from the mixed tweets by using Multinomial Naive Bayes and Support Vector Regression (SVR) Algorithm as a classifier.
Author Arora, Priyanka
Arora, Parul
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  fullname: Arora, Parul
  organization: Jaypee Institute of Information Technology,Electronics & Communication department,Noida,India
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Snippet Health care twitter analysis deals with the health related tweets through sentimental analysis by the patients themselves. The application of sentiment...
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StartPage 186
SubjectTerms Depression
Dictionaries
Diseases
Feature extraction
natural language processing
Sentiment analysis
Support vector machines
Twitter
Title Mining Twitter Data for Depression Detection
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