השוואת שיטות

	ניתוח שכיחות משותפת	ניתוח סנטימנט
תחום	כריית טקסט	כריית טקסט
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1957	—
הוגה השיטה	J.R. Firth (distributional principle)	—
סוג	Text-mining / distributional-semantics technique	NLP text-classification task
מקור מכונן	Firth, J.R. (1957). A Synopsis of Linguistic Theory. Studies in Linguistic Analysis. Oxford: Blackwell.	Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135.
כינויים	word co-occurrence, co-occurrence network, Kelime Eş-Oluşum Analizi	opinion mining, polarity detection, duygu analizi
קשורות	4	3
תקציר	Co-occurrence analysis is a text-mining technique that statistically counts the word pairs that appear together within a window or a sentence and uses their frequencies to reveal semantic maps and thematic structure. It rests on the distributional principle articulated by J.R. Firth in 1957 — that a word is characterised by the company it keeps.	Sentiment analysis, also called opinion mining, is a natural-language-processing task that detects the emotional tone of text — typically classifying it as positive, negative, or neutral. It turns unstructured opinion text into structured, quantifiable polarity signals using one of three families of approaches: sentiment lexicons, trained machine-learning classifiers, or pretrained transformer models.