Sentence examples for sentiment useful from inspiring English sources

Colburn offered his services, and Arnold requested detailed information about the route, including potential British naval threats, Indian sentiment, useful supply opportunities, and an estimate of how long it would take to construct bateaux sufficient for the contemplated force.

While mentions and sentiment are useful indicators of opinions towards a particular campaign, for advertisers to really understand the sales impact of their work, they need to show how many sales are likely to occur as a direct result of a campaign.

Such gloomy sentiments -- useful to the association in persuading the Federal Reserve to cut interest rates again and again -- stand in striking contrast to the more upbeat stories that many manufacturers tell about their current situation.

This semantic search is able to parse and incorporate, for example, sentiment about how useful an app has been and where it's been used, or when it has been slammed by consumers.

It didn't work for Gabriel as he appears to have done nothing since, but the sentiment might be useful.

In his past work, he's looked at visual sentiment analysis, a useful tool for analyzing social multimedia posts - those that incorporate, say, text and images - since text often doesn't convey the whole meaning of a post.

In May, Ethiopian Prime Minister Hailemariam Desalegn accused the ICC of racist bias and of "hunting Africans". That kind of sentiment could prove useful in the weeks to come, to counter the potential negative impression created by pictures of Mr Ruto in the dock.

While this scheme can provide acceptable performance in certain settings, it is unable to improve its performance or adapt to new domains, and it is usually labor-intensive to construct lexicons which are sufficiently complete to enable useful sentiment classification performance to be achieved.

Maybe this will convince them not to prank you this year... 5. Useful sentiments for the whole class.

Typically performed by supervised machine learning algorithms, sentiment analysis is highly useful for extracting subjective information from text documents online.

We find that sentiment analysis serves as a useful tool for automated defect discovery in the baby crib industry and create a supplementary set of "smoke terms" that are strong indicators of safety defects in online reviews of baby cribs.