系统梳理阿拉伯语情感分析现状与挑战，指明未来研究方向。
A comprehensive survey of contemporary Arabic sentiment analysis: Methods, Challenges, and Future Directions
- 系统回顾基于深度学习的阿拉伯语情感分析方法
- 指出现有研究在数据、模型和评估上的主要局限
- 适合对低资源语言情感分析感兴趣的学者参考
情感分析是自然语言处理中的热门子任务，通过计算方法从语言数据中提取情感、观点等主观信息。由于其在理解人类情感方面的重要性，近年来相关研究发展迅速。然而，多数方法集中于英语，阿拉伯语情感分析仍相对未被充分探索。本文全面综述了当代阿拉伯语情感分析的研究进展，识别现有文献中的挑战与局限，并提出未来研究方向。系统回顾了利用深度学习的阿拉伯语情感分析方法，将其置于更广泛的研究背景中，突出阿拉伯语情感分析相较于通用情感分析的差距。最后，总结了主要挑战与有前景的未来研究路径。
原文摘要 · Abstract (English)
Sentiment Analysis, a popular subtask of Natural Language Processing, employs computational methods to extract sentiment, opinions, and other subjective aspects from linguistic data. Given its crucial role in understanding human sentiment, research in sentiment analysis has witnessed significant growth in the recent years. However, the majority of approaches are aimed at the English language, and research towards Arabic sentiment analysis remains relatively unexplored. This paper presents a comprehensive and contemporary survey of Arabic Sentiment Analysis, identifies the challenges and limitations of existing literature in this field and presents avenues for future research. We present a systematic review of Arabic sentiment analysis methods, focusing specifically on research utilizing deep learning. We then situate Arabic Sentiment Analysis within the broader context, highlighting research gaps in Arabic sentiment analysis as compared to general sentiment analysis. Finally, we outline the main challenges and promising future directions for research in Arabic sentiment analysis.
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