TY - JOUR
T1 - A survey of opinion mining in Arabic
T2 - A comprehensive system perspective covering challenges and advances in tools, resources, models, applications, and visualizations
AU - Badaro, Gilbert
AU - Baly, Ramy
AU - Hajj, Hazem
AU - El-Hajj, Wassim
AU - Shaban, Khaled Bashir
AU - Habash, Nizar
AU - Al-Sallab, Ahmad
AU - Hamdi, Ali
N1 - Funding Information:
This work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Authors’ addresses: G. Badaro and H. Hajj, American University of Beirut, P.O.Box 11-0236 / Electrical and Computer Engineering Department, Riad El-Solh / Beirut 1107 2020, Lebanon; emails: {ggb05, hh63}@aub.edu.lb; R. Baly, Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America; email: baly@mit.edu; W. El-Hajj, American University of Beirut, P.O.Box 11-0236 / Computer Science Department, Riad El-Solh / Beirut 1107 2020, Lebanon; email: we07@aub.edu.lb; K. B. Shaban and A. Hamdi, Qatar University, P.O. Box: 2713 – Doha / Computer Science and Engineering Department, Qatar; emails: khaled.shaban@qu.edu.qa, alihamdif@gmail.com; N. Habash, Computer Science Department, New York University of Abu Dhabi, Saadiyat Marina District, Abu Dhabi, United Arab Emirates; email: nizar.habash@nyu.edu; A. Al-Sallab, Computer Engineering Department, Cairo University, 1 Gamaa Street, Giza 12613, Egypt; email: ahmad.elsallab@gmail.com. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2019 Association for Computing Machinery. 2375-4699/2019/05-ART27 $15.00 https://doi.org/10.1145/3295662
Funding Information:
This work was made possible by NPRP 6-716-1-138 grant from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/5
Y1 - 2019/5
N2 - Opinion-mining or sentiment analysis continues to gain interest in industry and academics. While there has been significant progress in developing models for sentiment analysis, the field remains an active area of research for many languages across the world, and in particular for the Arabic language, which is the fifth most-spoken language and has become the fourth most-used language on the Internet. With the flurry of research activity in Arabic opinion mining, several researchers have provided surveys to capture advances in the field. While these surveys capture a wealth of important progress in the field, the fast pace of advances in machine learning and natural language processing (NLP) necessitates a continuous need for a more up-to-date literature survey. The aim of this article is to provide a comprehensive literature survey for state-of-the-art advances in Arabic opinion mining. The survey goes beyond surveying previous works that were primarily focused on classification models. Instead, this article provides a comprehensive system perspective by covering advances in different aspects of an opinion-mining system, including advances in NLP software tools, lexical sentiment and corpora resources, classification models, and applications of opinion mining. It also presents future directions for opinion mining in Arabic. The survey also covers latest advances in the field, including deep learning advances in Arabic Opinion Mining. The article provides state-of-the-art information to help new or established researchers in the field as well as industry developers who aim to deploy an operational complete opinion-mining system. Key insights are captured at the end of each section for particular aspects of the opinion-mining system giving the reader a choice of focusing on particular aspects of interest.
AB - Opinion-mining or sentiment analysis continues to gain interest in industry and academics. While there has been significant progress in developing models for sentiment analysis, the field remains an active area of research for many languages across the world, and in particular for the Arabic language, which is the fifth most-spoken language and has become the fourth most-used language on the Internet. With the flurry of research activity in Arabic opinion mining, several researchers have provided surveys to capture advances in the field. While these surveys capture a wealth of important progress in the field, the fast pace of advances in machine learning and natural language processing (NLP) necessitates a continuous need for a more up-to-date literature survey. The aim of this article is to provide a comprehensive literature survey for state-of-the-art advances in Arabic opinion mining. The survey goes beyond surveying previous works that were primarily focused on classification models. Instead, this article provides a comprehensive system perspective by covering advances in different aspects of an opinion-mining system, including advances in NLP software tools, lexical sentiment and corpora resources, classification models, and applications of opinion mining. It also presents future directions for opinion mining in Arabic. The survey also covers latest advances in the field, including deep learning advances in Arabic Opinion Mining. The article provides state-of-the-art information to help new or established researchers in the field as well as industry developers who aim to deploy an operational complete opinion-mining system. Key insights are captured at the end of each section for particular aspects of the opinion-mining system giving the reader a choice of focusing on particular aspects of interest.
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U2 - 10.1145/3295662
DO - 10.1145/3295662
M3 - Review article
AN - SCOPUS:85065785888
SN - 2375-4699
VL - 18
JO - ACM Transactions on Asian and Low-Resource Language Information Processing
JF - ACM Transactions on Asian and Low-Resource Language Information Processing
IS - 3
M1 - 27
ER -