Salīdzināt metodes

	Sentiment Analysis in Communication	LIWC Text Analysis
Nozare	Communication	Communication
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2010	2001
Autors	Adapted into communication research from NLP / opinion mining	James W. Pennebaker and colleagues
Tips	Automated classification of message valence/tone	Dictionary-based quantitative text analysis
Pirmavots	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.	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.
Citi nosaukumi	Opinion mining in communication, Tone analysis, Media sentiment analysis, İletişimde Duygu Analizi	Linguistic Inquiry and Word Count, LIWC dictionary analysis, Word-count text analysis, LIWC Metin Analizi
Saistītās	5	4
Kopsavilkums	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.	LIWC (Linguistic Inquiry and Word Count) is a dictionary-based text-analysis method that counts the proportion of words in a text falling into psychologically and linguistically meaningful categories — such as positive emotion, cognitive processing, social references, and function words like pronouns. Developed by James Pennebaker and colleagues, it has become a workhorse for quantifying the psychological and rhetorical character of communication at scale.