A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms

Anusha; Savitha A. Shenoy; S. V. Harish

doi:10.1109/INOCON57975.2023.10101258

A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms

Anusha^*
, Savitha A. Shenoy
, S. V. Harish

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

One of the main factor contributing to mental illness, which has been linked to an increased risk of dying young is depression. Additionally, it significantly contributes to suicide ideation. Although there are many underlying reasons of depression, social networking sites play a key part in raising the likelihood of depression. In recent years social media has become the integral part of our daily lives. User reflects his internal life in the content he shares in his social media platform like twitter. People share happy incidents, joyful memories and sad moments through tweets. Thus it is possible to forecast depression in people using Twitter data. Various machine learning techniques have been employed to analyze these data. The algorithms employed are Naïve Bayes and Logistic Regression. Those algorithms will produce intended outcomes.

Original language	English
Title of host publication	2023 2nd International Conference for Innovation in Technology, INOCON 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350320923
DOIs	https://doi.org/10.1109/INOCON57975.2023.10101258
Publication status	Published - 2023
Event	2nd International Conference for Innovation in Technology, INOCON 2023 - Bangalore, India Duration: 03-03-2023 → 05-03-2023

Publication series

Name	2023 2nd International Conference for Innovation in Technology, INOCON 2023

Conference

Conference	2nd International Conference for Innovation in Technology, INOCON 2023
Country/Territory	India
City	Bangalore
Period	03-03-23 → 05-03-23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications
Information Systems
Information Systems and Management
Energy Engineering and Power Technology
Safety, Risk, Reliability and Quality

Access to Document

10.1109/INOCON57975.2023.10101258

Cite this

Anusha, Shenoy, S. A., & Harish, S. V. (2023). A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms. In 2023 2nd International Conference for Innovation in Technology, INOCON 2023 (2023 2nd International Conference for Innovation in Technology, INOCON 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INOCON57975.2023.10101258

@inproceedings{7628549fefbe40ba9507a7a5686cfc40,

title = "A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms",

abstract = "One of the main factor contributing to mental illness, which has been linked to an increased risk of dying young is depression. Additionally, it significantly contributes to suicide ideation. Although there are many underlying reasons of depression, social networking sites play a key part in raising the likelihood of depression. In recent years social media has become the integral part of our daily lives. User reflects his internal life in the content he shares in his social media platform like twitter. People share happy incidents, joyful memories and sad moments through tweets. Thus it is possible to forecast depression in people using Twitter data. Various machine learning techniques have been employed to analyze these data. The algorithms employed are Na{\"i}ve Bayes and Logistic Regression. Those algorithms will produce intended outcomes.",

author = "Anusha and Shenoy, \{Savitha A.\} and Harish, \{S. V.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2nd International Conference for Innovation in Technology, INOCON 2023 ; Conference date: 03-03-2023 Through 05-03-2023",

year = "2023",

doi = "10.1109/INOCON57975.2023.10101258",

language = "English",

series = "2023 2nd International Conference for Innovation in Technology, INOCON 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 2nd International Conference for Innovation in Technology, INOCON 2023",

address = "United States",

}

Anusha, Shenoy, SA & Harish, SV 2023, A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms. in 2023 2nd International Conference for Innovation in Technology, INOCON 2023. 2023 2nd International Conference for Innovation in Technology, INOCON 2023, Institute of Electrical and Electronics Engineers Inc., 2nd International Conference for Innovation in Technology, INOCON 2023, Bangalore, India, 03-03-23. https://doi.org/10.1109/INOCON57975.2023.10101258

A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms. / Anusha; Shenoy, Savitha A.; Harish, S. V.
2023 2nd International Conference for Innovation in Technology, INOCON 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 2nd International Conference for Innovation in Technology, INOCON 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms

AU - Anusha,

AU - Shenoy, Savitha A.

AU - Harish, S. V.

PY - 2023

Y1 - 2023

N2 - One of the main factor contributing to mental illness, which has been linked to an increased risk of dying young is depression. Additionally, it significantly contributes to suicide ideation. Although there are many underlying reasons of depression, social networking sites play a key part in raising the likelihood of depression. In recent years social media has become the integral part of our daily lives. User reflects his internal life in the content he shares in his social media platform like twitter. People share happy incidents, joyful memories and sad moments through tweets. Thus it is possible to forecast depression in people using Twitter data. Various machine learning techniques have been employed to analyze these data. The algorithms employed are Naïve Bayes and Logistic Regression. Those algorithms will produce intended outcomes.

AB - One of the main factor contributing to mental illness, which has been linked to an increased risk of dying young is depression. Additionally, it significantly contributes to suicide ideation. Although there are many underlying reasons of depression, social networking sites play a key part in raising the likelihood of depression. In recent years social media has become the integral part of our daily lives. User reflects his internal life in the content he shares in his social media platform like twitter. People share happy incidents, joyful memories and sad moments through tweets. Thus it is possible to forecast depression in people using Twitter data. Various machine learning techniques have been employed to analyze these data. The algorithms employed are Naïve Bayes and Logistic Regression. Those algorithms will produce intended outcomes.

UR - https://www.scopus.com/pages/publications/85158055397

UR - https://www.scopus.com/pages/publications/85158055397#tab=citedBy

U2 - 10.1109/INOCON57975.2023.10101258

DO - 10.1109/INOCON57975.2023.10101258

M3 - Conference contribution

AN - SCOPUS:85158055397

T3 - 2023 2nd International Conference for Innovation in Technology, INOCON 2023

BT - 2023 2nd International Conference for Innovation in Technology, INOCON 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Conference for Innovation in Technology, INOCON 2023

Y2 - 3 March 2023 through 5 March 2023

ER -

A Study to Detect Emotions from Twitter Text Using Machine Learning Algorithms

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

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