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Sentiment Analysis in Communication×Konteksa analīze×
NozareCommunicationKvalitatīvās metodes
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads2010Systematised through Krippendorff's methodology work; 4th edition 2018
AutorsAdapted into communication research from NLP / opinion miningKlaus Krippendorff (systematic formulation); roots in early 20th-century communications research
TipsAutomated classification of message valence/toneQualitative / mixed-method research technique
PirmavotsTausczik, 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. DOI ↗Krippendorff, K. (2018). Content Analysis: An Introduction to Its Methodology (4th ed.). Sage. ISBN: 978-1506395661
Citi nosaukumiOpinion mining in communication, Tone analysis, Media sentiment analysis, İletişimde Duygu Analiziİçerik Analizi, systematic content coding, quantitative content analysis
Saistītās55
KopsavilkumsSentiment 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.Content analysis is a systematic research technique for reducing text, visual, or media material into coded categories so that patterns can be counted, compared, and interpreted. Formalised by Klaus Krippendorff in his widely cited methodology textbook (latest edition 2018), the method sits at the boundary of qualitative and quantitative inquiry: it imposes structured, replicable coding on inherently meaning-laden material.
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ScholarGateSalīdzināt metodes: Sentiment Analysis in Communication · Content Analysis. Izgūts 2026-06-24 no https://scholargate.app/lv/compare