Sentiment analysis of twitter data related to Rinca Island development using Doc2Vec and SVM and logistic regression as classifier

Tirta Hema Jaya Hidayat; Yova Ruldeviyani; Achmad Rizki Aditama; Gusti Raditia Madya; Ade Wija Nugraha; Muhammad Wijaya Adisaputra

doi:10.1016/j.procs.2021.12.187

Sentiment analysis of twitter data related to Rinca Island development using Doc2Vec and SVM and logistic regression as classifier

Tirta Hema Jaya Hidayat, Yova Ruldeviyani, Achmad Rizki Aditama, Gusti Raditia Madya, Ade Wija Nugraha, Muhammad Wijaya Adisaputra

Department of Computer Science

Research output: Contribution to journal › Conference article › peer-review

60 Citations (Scopus)

Abstract

Development on Rinca Island by the Indonesian Government has received a lot of reaction from the community. Masses expressed their opinion through social media, especially Twitter regarding the matter. The research was conducted to analyze the public's sentiment about this development which was divided into three categories: pro, contra, and neutral. There are two Doc2Vec models used in this research, the distributed model, and the distributed bag of words, and using support vector machines and logistic regression as classifiers. Each combination of the models and classifier has an accuracy rate above 75% and shows that almost all are against the development of Rinca Island.

Original language	English
Pages (from-to)	660-667
Number of pages	8
Journal	Procedia Computer Science
Volume	197
DOIs	https://doi.org/10.1016/j.procs.2021.12.187
Publication status	Published - 2021
Event	6th Information Systems International Conference, ISICO 2021 - Virtual, Online, Italy Duration: 7 Aug 2021 → 8 Aug 2021

Keywords

Doc2Vec
Logistic regression
Natural languange processing
Sentiment analysis
Support vector machine

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10.1016/j.procs.2021.12.187

Cite this

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title = "Sentiment analysis of twitter data related to Rinca Island development using Doc2Vec and SVM and logistic regression as classifier",

abstract = "Development on Rinca Island by the Indonesian Government has received a lot of reaction from the community. Masses expressed their opinion through social media, especially Twitter regarding the matter. The research was conducted to analyze the public's sentiment about this development which was divided into three categories: pro, contra, and neutral. There are two Doc2Vec models used in this research, the distributed model, and the distributed bag of words, and using support vector machines and logistic regression as classifiers. Each combination of the models and classifier has an accuracy rate above 75% and shows that almost all are against the development of Rinca Island.",

keywords = "Doc2Vec, Logistic regression, Natural languange processing, Sentiment analysis, Support vector machine",

author = "Hidayat, {Tirta Hema Jaya} and Yova Ruldeviyani and Aditama, {Achmad Rizki} and Madya, {Gusti Raditia} and Nugraha, {Ade Wija} and Adisaputra, {Muhammad Wijaya}",

note = "Publisher Copyright: {\textcopyright} 2021 The Authors. Published by Elsevier B.V.; 6th Information Systems International Conference, ISICO 2021 ; Conference date: 07-08-2021 Through 08-08-2021",

year = "2021",

doi = "10.1016/j.procs.2021.12.187",

language = "English",

volume = "197",

pages = "660--667",

journal = "Procedia Computer Science",

issn = "1877-0509",

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T1 - Sentiment analysis of twitter data related to Rinca Island development using Doc2Vec and SVM and logistic regression as classifier

AU - Hidayat, Tirta Hema Jaya

AU - Ruldeviyani, Yova

AU - Aditama, Achmad Rizki

AU - Madya, Gusti Raditia

AU - Nugraha, Ade Wija

AU - Adisaputra, Muhammad Wijaya

PY - 2021

Y1 - 2021

N2 - Development on Rinca Island by the Indonesian Government has received a lot of reaction from the community. Masses expressed their opinion through social media, especially Twitter regarding the matter. The research was conducted to analyze the public's sentiment about this development which was divided into three categories: pro, contra, and neutral. There are two Doc2Vec models used in this research, the distributed model, and the distributed bag of words, and using support vector machines and logistic regression as classifiers. Each combination of the models and classifier has an accuracy rate above 75% and shows that almost all are against the development of Rinca Island.

AB - Development on Rinca Island by the Indonesian Government has received a lot of reaction from the community. Masses expressed their opinion through social media, especially Twitter regarding the matter. The research was conducted to analyze the public's sentiment about this development which was divided into three categories: pro, contra, and neutral. There are two Doc2Vec models used in this research, the distributed model, and the distributed bag of words, and using support vector machines and logistic regression as classifiers. Each combination of the models and classifier has an accuracy rate above 75% and shows that almost all are against the development of Rinca Island.

KW - Doc2Vec

KW - Logistic regression

KW - Natural languange processing

KW - Sentiment analysis

KW - Support vector machine

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U2 - 10.1016/j.procs.2021.12.187

DO - 10.1016/j.procs.2021.12.187

M3 - Conference article

AN - SCOPUS:85123758919

SN - 1877-0509

VL - 197

SP - 660

EP - 667

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - 6th Information Systems International Conference, ISICO 2021

Y2 - 7 August 2021 through 8 August 2021

ER -

Sentiment analysis of twitter data related to Rinca Island development using Doc2Vec and SVM and logistic regression as classifier

Abstract

Keywords

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