相关论文: A System for Extracting Sentiment from Large-Scale…

Sentiment analysis is a highly subjective and challenging task. Its complexity further increases when applied to the Arabic language, mainly because of the large variety of dialects that are unstandardized and widely used in the Web,…

Sentiment Analysis (SA) is an indispensable task for many real-world applications. Compared to limited resourced languages (i.e., Arabic, Bengali), most of the research on SA are conducted for high resourced languages (i.e., English,…

With the expansion in tenders on the Internet and social media, Arabic Sentiment Analysis (ASA) has assumed a significant position in the field of text mining study and has since remained used to explore the sentiments of users about…

Opinion mining aims at extracting useful subjective information from reliable amounts of text. Opinion mining holder recognition is a task that has not been considered yet in Arabic Language. This task essentially requires deep…

Statistical machine translation for dialectal Arabic is characterized by a lack of data since data acquisition involves the transcription and translation of spoken language. In this study we develop techniques for extracting parallel data…

Since their inception, transformer-based language models have led to impressive performance gains across multiple natural language processing tasks. For Arabic, the current state-of-the-art results on most datasets are achieved by the…

Multimodal Sentiment Analysis (MSA) has recently become a centric research direction for many real-world applications. This proliferation is due to the fact that opinions are central to almost all human activities and are key influencers of…

Recommender systems nowadays are playing an important role in the delivery of services and information to users. Sentiment analysis (also known as opinion mining) is the process of determining the attitude of textual opinions, whether they…

Social media such as Twitter, Facebook, etc. has led to a generated growing number of comments that contains users opinions. Sentiment analysis research deals with these comments to extract opinions which are positive or negative. Arabic…

Arabic is one of the oldest languages still in use today. As a result, several Arabic-speaking regions have developed dialects that are unique to them. Dialect and emotion recognition have various uses in Arabic text analysis, such as…

Sentiment analysis (SA) has been, and is still, a thriving research area. However, the task of Arabic sentiment analysis (ASA) is still underrepresented in the body of research. This study offers the first in-depth and in-breadth analysis…

Extracting useful information for sentiment analysis and classification problems from a big amount of user-generated feedback, such as restaurant reviews, is a crucial task of natural language processing, which is not only for customer…

Rapid increase in the volume of sentiment rich social media on the web has resulted in an increased interest among researchers regarding Sentimental Analysis and opinion mining. However, with so much social media available on the web,…

Recent studies showed a huge interest in social networks sentiment analysis. Twitter, which is a microblogging service, can be a great source of information on how the users feel about a certain topic, or what their opinion is regarding a…

Although, the fair amount of works in sentiment analysis (SA) and opinion mining (OM) systems in the last decade and with respect to the performance of these systems, but it still not desired performance, especially for morphologically-Rich…

Unlike other languages, the Arabic language has a morphological complexity which makes the Arabic sentiment analysis is a challenging task. Moreover, the presence of the dialects in the Arabic texts have made the sentiment analysis task is…

Sentiment analysis aims to extract people's emotions and opinion from their comments on the web. It widely used in businesses to detect sentiment in social data, gauge brand reputation, and understand customers. Most of articles in this…

Social media is increasingly used by humans to express their feelings and opinions in the form of short text messages. Detecting sentiments in the text has a wide range of applications including identifying anxiety or depression of…

We introduce LABR, the largest sentiment analysis dataset to-date for the Arabic language. It consists of over 63,000 book reviews, each rated on a scale of 1 to 5 stars. We investigate the properties of the dataset, and present its…

In recent years, Large Language Models have revolutionized the field of natural language processing, showcasing an impressive rise predominantly in English-centric domains. These advancements have set a global benchmark, inspiring…