Towards Discovering the Sentiment Holder in Arabic Text

Dahab, Mohammed; Asmari, Salma Al

doi:10.5120/19621-1301

Cited by 3 publications

(2 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the recent past, there have been efforts to provide informative surveys of trends and challenges in Arabic sentiment analysis [22,34,53,92,97,99,114,142,161,163,233,239,262,302,305]. An early survey [277] covered early and limited work in the field up to 2012.…”

Section: Introductionmentioning

confidence: 99%

A Survey of Opinion Mining in Arabic

Badaro

Baly

Hajj

et al. 2019

ACM Trans. Asian Low-Resour. Lang. Inf. Process.

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

A Survey of Opinion Mining in Arabic

Badaro

Baly

Hajj

et al. 2019

ACM Trans. Asian Low-Resour. Lang. Inf. Process.

View full text Add to dashboard Cite

show abstract

“…This definition converting unstructured text into structured data and provides the accurate information for opinions analysis [7]. Dahab and Al Asmari [8] The SA aspect identification focuses more on feature-level sentiment analysis, which relied on the idea that an opinion contains a sentiment polarity (positive or negative) and a feature of products.…”

Section: The Problem Of Sentiment Analysismentioning

confidence: 99%

Sentiment Detection, Recognition and Aspect Identification

Alasmari¹,

Dahab²

2017

IJCA

Self Cite

View full text Add to dashboard Cite

Sentiment analysis is the study of people's opinions, attitudes, feelings, and emotions discuss any object such as entities, events, topics, product, issues, services, etc. are respected for extraction of useful subjective information out of the text. The task is challenging and considered for customers and producers, for instance, Customers need to have general ideas about products, and companies need to know customers' needs and the opportunity to investigate and analyze those opinions towards their products and services. The increasing growth of the social network sites generating a big resource of social data. So, researchers considering about harnessing the effeteness of social media and sentiment analysis. These recent studies classified according to their contributions in the different SA methods. The main target of this paper is to give the illustration of the current trend of research in the sentiment analysis Detection, Recognition, Aspect Identification.

show abstract