Improving Sentiment Analysis of Arabic Tweets

Abdulrahman Alruban; Muhammed Abduallah; Gueltoum Bendiab; Stavros Shiaeles; Marco Palomino

doi:10.1007/978-981-15-4825-3_12

Improving Sentiment Analysis of Arabic Tweets

Abdulrahman Alruban, Muhammed Abduallah, Gueltoum Bendiab, Stavros Shiaeles^* (Corresponding Author), Marco Palomino

^*Corresponding author for this work

Computing Science

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

1 Citation (Scopus)

Abstract

Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.

Original language	English
Title of host publication	Security in Computing and Communications
Subtitle of host publication	7th International Symposium, SSCC 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers
Editors	Sabu M. Thampi, Gregorio Martinez Perez, Ryan Ko, Danda B. Rawat
Publisher	Springer
Pages	146-158
Number of pages	13
ISBN (Print)	9789811548246, 9789811548253
DOIs	https://doi.org/10.1007/978-981-15-4825-3_12
Publication status	Published - 26 Apr 2020
Event	Security in Computing and Communications: 7th International Symposium - Trivandrum, India Duration: 18 Dec 2019 → 21 Dec 2019

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	1208
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	Security in Computing and Communications
Abbreviated title	SSCC 2019
Country/Territory	India
City	Trivandrum
Period	18/12/19 → 21/12/19

Access to Document

10.1007/978-981-15-4825-3_12Licence: Unspecified

Cite this

Alruban, A., Abduallah, M., Bendiab, G., Shiaeles, S., & Palomino, M. (2020). Improving Sentiment Analysis of Arabic Tweets. In S. M. Thampi, G. M. Perez, R. Ko, & D. B. Rawat (Eds.), Security in Computing and Communications: 7th International Symposium, SSCC 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers (pp. 146-158). (Communications in Computer and Information Science; Vol. 1208). Springer . https://doi.org/10.1007/978-981-15-4825-3_12

Improving Sentiment Analysis of Arabic Tweets. / Alruban, Abdulrahman; Abduallah, Muhammed; Bendiab, Gueltoum et al.
Security in Computing and Communications: 7th International Symposium, SSCC 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers. ed. / Sabu M. Thampi; Gregorio Martinez Perez; Ryan Ko; Danda B. Rawat. Springer , 2020. p. 146-158 (Communications in Computer and Information Science; Vol. 1208).

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

Alruban, A, Abduallah, M, Bendiab, G, Shiaeles, S & Palomino, M 2020, Improving Sentiment Analysis of Arabic Tweets. in SM Thampi, GM Perez, R Ko & DB Rawat (eds), Security in Computing and Communications: 7th International Symposium, SSCC 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers. Communications in Computer and Information Science, vol. 1208, Springer , pp. 146-158, Security in Computing and Communications, Trivandrum, India, 18/12/19. https://doi.org/10.1007/978-981-15-4825-3_12

Alruban A, Abduallah M, Bendiab G, Shiaeles S, Palomino M. Improving Sentiment Analysis of Arabic Tweets. In Thampi SM, Perez GM, Ko R, Rawat DB, editors, Security in Computing and Communications: 7th International Symposium, SSCC 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers. Springer . 2020. p. 146-158. (Communications in Computer and Information Science). doi: 10.1007/978-981-15-4825-3_12

Alruban, Abdulrahman ; Abduallah, Muhammed ; Bendiab, Gueltoum et al. / Improving Sentiment Analysis of Arabic Tweets. Security in Computing and Communications: 7th International Symposium, SSCC 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers. editor / Sabu M. Thampi ; Gregorio Martinez Perez ; Ryan Ko ; Danda B. Rawat. Springer , 2020. pp. 146-158 (Communications in Computer and Information Science).

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abstract = "Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.",

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AB - Twitter popularity grew rapidly the last years and become a place where people express their opinions, views, feelings and ideas. This popularity and the vast amount of information triggered the interest of companies as well as researchers on sentiment analysis trying to export meaningful results from this information. Even if there is a tremendous amount of work on Latin originated languages, such as English, there is not much research available on native languages such as Arabic, Greek etc. This research aims to develop a new system able to bridge the gap in Arabic users and sentiment analysis by providing a novel dictionary able to classify Arabic Tweets with different Arabic dialects and emotions, as positive, negative or natural. The study provides a quantitative analysis to gain an in-depth understanding of the phenomenon under investigation and the findings of the study show that the designed system is very promising.

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Improving Sentiment Analysis of Arabic Tweets

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