Sentence examples for used sentiment from inspiring English sources

Some scholars have used "sentiment classification" techniques to analyze what was being said about authors in their day — pairing, for example, the reigning Galsworthy against the ascendant D. H. Lawrence.

SpeechCoach.Ai takes into account your speaking pace, the number of filler words you used, sentiment analysis and grammatical mistakes.

Hume, in contrast, often used "sentiment" for the class of refined and reflective emotions that are the basis for our moral and aesthetic judgments.

The feedback includes features like your pace of talking, how many filler words you used, sentiment analysis and number of grammatical mistakes.

Bouktif et al. (2013) used sentiment data from Twitter to predict stock prices using Ant Colony based Approach that integrated multiple single Bayesian classifiers.

Empatika used sentiment analysis to analyze around 500,000 reviews and see what reviewers were saying about some popular App Store titles, including Facebook, Twitter, YouTube, Instagram and more.

Twitter introduced an Election Index using sentiment analysis to show us which candidates fared better in terms of how Twitter users were discussing them, day by day.

We use sentiment analysis as a lens that allows us to see how the emotive words in a text shape the overall content.

Ms. Kooren uses Sentiment Metrics and is alerted when Velvet Palate or any of her specified search terms are mentioned.

On election night on Tuesday, CNN plans to use sentiment analysis to identify and track themes that gain traction online.

Using sentiment analysis tool, Robinson found that: "Trump's Android account uses about 40%-80 40%-80words related to disgust, sadness, fear, anger, and other "negative" sentiments than the iPhone account does.