قارن الطرق

	تعدين الآراء	تصنيف النصوص
المجال	تنقيب النصوص	تنقيب النصوص
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	2012	—
صاحب الطريقة	Bing Liu	—
النوع	NLP information-extraction task	Supervised NLP classification task
المصدر التأسيسي	Liu, B. (2012). Sentiment Analysis and Opinion Mining. Morgan & Claypool.	Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer.
الأسماء البديلة	aspect-based sentiment analysis, opinion extraction, Görüş Madenciliği (Opinion Mining)	text categorization, document classification, topic classification, metin sınıflandırma
ذات صلة	3	4
الملخص	Opinion mining is a natural-language-processing task that systematically extracts and analyses user opinions about a product, service, or topic — identifying the specific features (aspects) being discussed, the sentiment expressed toward each, and the opinion holders. Consolidated by Bing Liu (2012), it goes beyond a single document-level label to produce structured aspect–opinion–holder records.	Text classification, also called text categorization, is a supervised natural-language-processing task that automatically assigns documents to predefined categories. Building on the support-vector-machine approach to text categorization established by Joachims (1998) and consolidated in the text-mining literature by Aggarwal and Zhai (2012), it powers tasks such as spam detection and topic classification by learning from labelled examples.