Virtual emotion detection by sentiment analysis

Virtual emotion detection by sentiment analysis

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Publicado en 3C TIC – Volume 11 Issue 2 (Ed. 41)




As websites, social networks, blogs, and online portals proliferate on the internet, authors are producing reviews, opinions, ideas, ratings, and feedback. The emotional content of this writer may be about things like books, people, hotels, items, studies, events, and so on. These emotions have great value for businesses, for governments, and for people. The majority of the writer-generated material requires the usage of text mining algorithms and sentiment analysis, even if this information is meant to be instructive. Sentiment Analysis is a technique in Natural Language Processing (NLP) that tries to identify and extract assessments communicated within a given text. This paper intends to execute different content handling strategies in NLP and use of Valence Aware Dictionary for Sentiment Reasoning (VADER) Model that is sensitive to both polarity (positive/negative) and intensity (strength) of emotion.


Palabras clave


Natural Language Processing (NLP), Polarity Intensity, Sentiment Analysis, Virtual Emotion Detection, VADER.

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