One of the mysteries of the English language finally explained.
The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral.‘companies have key lessons to learn about harnessing the power of social media and sentiment analysis’
- ‘Using sentiment analysis, we assess the strategies that the groups used in their discourse one year before the election and immediately after the election.’
- ‘For many companies, the burgeoning text analytics approach of sentiment analysis is becoming a critical component of their overall strategy, giving them a much-needed assist to stay responsive to customers, market opportunities and trends.’
- ‘So far we have not found an effective way to significantly improve search using sentiment analysis.’
- ‘Such a "sentiment analysis" is intended to identify potential threats to the nation, security officials said.’
- ‘I doubt they're doing a lot of sentiment analysis yet on social media (at least for ranking purposes), but it's bound to happen.’
- ‘Until such time as Google et al can 'get' sarcasm, sentiment analysis is not even worth talking about.’
- ‘Through sentiment analysis, if a computer detected that the person using it was angry, it could play some happy music to cheer them up.’
- ‘Use sentiment analysis to identify negative remarks and turn negative comments into negative votes.’
- ‘The Natural Language Toolkit, for example, has a movie reviews corpus you can use for sentiment analysis.’
- ‘Thelwall hopes that in the future sentiment analysis could help computers detect their users' moods so they can react accordingly.’
- ‘Recall that the idea of contrarian sentiment analysis is to measure the pulse of the speculative option crowd.’
- ‘Sentiment analysis can also struggle to identify irony or sarcasm, creating the risk that somebody tweeting "I don't see enough of him on TV" might get an ad that reflects exactly what they say and not what they mean.’
- ‘Using the innovative techniques of sentiment analysis, we determined the distribution of words used to express positive and negative emotions and behaviors about racial and ethnic relations as expressed in the blogs of hate groups.’
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