Sentiment analysis based on appraisal theory for assessing incumbent electability

Canrakerta; Pamuji Lasiyanto Putro; Zikri Irfandi; Nur Fitriah Ayuning Budi; Achmad Nizar Hidayanto

doi:10.1109/EECSI.2018.8752940

Sentiment analysis based on appraisal theory for assessing incumbent electability

Canrakerta, Pamuji Lasiyanto Putro, Zikri Irfandi, Nur Fitriah Ayuning Budi, Achmad Nizar Hidayanto

Department of Computer Science

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

1 Citation (Scopus)

Abstract

Sentiment analysis is a useful study for determining opinions by classifying text. The document used in the research comes from Twitter about public opinion about community satisfaction related to performance of incumbent. The method used is Appraisal Theory. The data used are 1587 for Jokowi related data, 1774 for Ministry related data, and 1337 government related data. The result of data analysis from this research is that people have positive sentiments for incumbent. Innovation is a term that has the highest positive sentiment, whereas imaging is the term that has the lowest negative sentiment.

Original language	English
Title of host publication	Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018
Editors	Deris Stiawan, Imam Much Ibnu Subroto, Munawar A. Riyadi, Christian Sri Kusuma Aditya, Zulfatman Has, Anton Yudhana, Agus Eko Minarno
Publisher	Institute of Advanced Engineering and Science (IAES)
Pages	101-106
Number of pages	6
ISBN (Electronic)	9781538684023
DOIs	https://doi.org/10.1109/EECSI.2018.8752940
Publication status	Published - 1 Oct 2018
Event	5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018 - Malang, Indonesia Duration: 16 Oct 2018 → 18 Oct 2018

Publication series

Name	International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
Volume	2018-October
ISSN (Print)	2407-439X

Conference

Conference	5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018
Country/Territory	Indonesia
City	Malang
Period	16/10/18 → 18/10/18

Keywords

Appraisal theory
sentiment analysis
Twitter

Access to Document

10.1109/EECSI.2018.8752940

Cite this

Canrakerta, Putro, P. L., Irfandi, Z., Budi, N. F. A., & Hidayanto, A. N. (2018). Sentiment analysis based on appraisal theory for assessing incumbent electability. In D. Stiawan, I. M. I. Subroto, M. A. Riyadi, C. S. K. Aditya, Z. Has, A. Yudhana, & A. E. Minarno (Eds.), Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018 (pp. 101-106). (International Conference on Electrical Engineering, Computer Science and Informatics (EECSI); Vol. 2018-October). Institute of Advanced Engineering and Science (IAES). https://doi.org/10.1109/EECSI.2018.8752940

Canrakerta ; Putro, Pamuji Lasiyanto ; Irfandi, Zikri et al. / Sentiment analysis based on appraisal theory for assessing incumbent electability. Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018. editor / Deris Stiawan ; Imam Much Ibnu Subroto ; Munawar A. Riyadi ; Christian Sri Kusuma Aditya ; Zulfatman Has ; Anton Yudhana ; Agus Eko Minarno. Institute of Advanced Engineering and Science (IAES), 2018. pp. 101-106 (International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)).

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title = "Sentiment analysis based on appraisal theory for assessing incumbent electability",

abstract = "Sentiment analysis is a useful study for determining opinions by classifying text. The document used in the research comes from Twitter about public opinion about community satisfaction related to performance of incumbent. The method used is Appraisal Theory. The data used are 1587 for Jokowi related data, 1774 for Ministry related data, and 1337 government related data. The result of data analysis from this research is that people have positive sentiments for incumbent. Innovation is a term that has the highest positive sentiment, whereas imaging is the term that has the lowest negative sentiment.",

keywords = "Appraisal theory, sentiment analysis, Twitter",

author = "Canrakerta and Putro, {Pamuji Lasiyanto} and Zikri Irfandi and Budi, {Nur Fitriah Ayuning} and Hidayanto, {Achmad Nizar}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018 ; Conference date: 16-10-2018 Through 18-10-2018",

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doi = "10.1109/EECSI.2018.8752940",

language = "English",

series = "International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)",

publisher = "Institute of Advanced Engineering and Science (IAES)",

pages = "101--106",

editor = "Deris Stiawan and Subroto, {Imam Much Ibnu} and Riyadi, {Munawar A.} and Aditya, {Christian Sri Kusuma} and Zulfatman Has and Anton Yudhana and Minarno, {Agus Eko}",

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Canrakerta, Putro, PL, Irfandi, Z, Budi, NFA & Hidayanto, AN 2018, Sentiment analysis based on appraisal theory for assessing incumbent electability. in D Stiawan, IMI Subroto, MA Riyadi, CSK Aditya, Z Has, A Yudhana & AE Minarno (eds), Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018. International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), vol. 2018-October, Institute of Advanced Engineering and Science (IAES), pp. 101-106, 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018, Malang, Indonesia, 16/10/18. https://doi.org/10.1109/EECSI.2018.8752940

Sentiment analysis based on appraisal theory for assessing incumbent electability. / Canrakerta; Putro, Pamuji Lasiyanto; Irfandi, Zikri et al.
Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018. ed. / Deris Stiawan; Imam Much Ibnu Subroto; Munawar A. Riyadi; Christian Sri Kusuma Aditya; Zulfatman Has; Anton Yudhana; Agus Eko Minarno. Institute of Advanced Engineering and Science (IAES), 2018. p. 101-106 (International Conference on Electrical Engineering, Computer Science and Informatics (EECSI); Vol. 2018-October).

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

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AU - Hidayanto, Achmad Nizar

PY - 2018/10/1

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N2 - Sentiment analysis is a useful study for determining opinions by classifying text. The document used in the research comes from Twitter about public opinion about community satisfaction related to performance of incumbent. The method used is Appraisal Theory. The data used are 1587 for Jokowi related data, 1774 for Ministry related data, and 1337 government related data. The result of data analysis from this research is that people have positive sentiments for incumbent. Innovation is a term that has the highest positive sentiment, whereas imaging is the term that has the lowest negative sentiment.

AB - Sentiment analysis is a useful study for determining opinions by classifying text. The document used in the research comes from Twitter about public opinion about community satisfaction related to performance of incumbent. The method used is Appraisal Theory. The data used are 1587 for Jokowi related data, 1774 for Ministry related data, and 1337 government related data. The result of data analysis from this research is that people have positive sentiments for incumbent. Innovation is a term that has the highest positive sentiment, whereas imaging is the term that has the lowest negative sentiment.

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Canrakerta, Putro PL, Irfandi Z, Budi NFA, Hidayanto AN. Sentiment analysis based on appraisal theory for assessing incumbent electability. In Stiawan D, Subroto IMI, Riyadi MA, Aditya CSK, Has Z, Yudhana A, Minarno AE, editors, Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018. Institute of Advanced Engineering and Science (IAES). 2018. p. 101-106. (International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)). doi: 10.1109/EECSI.2018.8752940

Sentiment analysis based on appraisal theory for assessing incumbent electability

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