방법 비교

	Sentiment Analysis in Communication	Manifest Content Analysis
분야	Communication	Communication
계열	Process / pipeline	Process / pipeline
기원 연도	2010	1952
창시자	Adapted into communication research from NLP / opinion mining	Bernard Berelson; codified by Klaus Krippendorff
유형	Automated classification of message valence/tone	Systematic quantitative coding of explicit message content
원전	Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29(1), 24–54.	Krippendorff, K. (2004). Content Analysis: An Introduction to Its Methodology (2nd ed.). Thousand Oaks, CA: Sage. ISBN: 9780761915454
별칭	Opinion mining in communication, Tone analysis, Media sentiment analysis, İletişimde Duygu Analizi	Quantitative manifest coding, Surface-content analysis, Manifest-level content analysis, Berelson content analysis
관련	5	5
요약	Sentiment analysis is the automated estimation of the valence — positive, negative, or neutral tone — of communication messages, adapted from natural-language processing into a core measurement technique for media and communication research. It lets scholars quantify the tone of news coverage, the affect of social-media discourse, or audience reactions across corpora far too large for hand coding, while treating tone as a measurable, validatable construct.	Manifest content analysis is a quantitative research technique that systematically counts the explicit, surface-level features of communication messages — words, sources, themes, images, or actors that are directly visible in the text or media artifact — according to a predefined coding scheme. Rooted in Bernard Berelson's classic definition of content analysis as the 'objective, systematic, and quantitative description of the manifest content of communication,' it is one of the foundational empirical methods of mass communication and media research.