Sentence examples for sentiment of the message from inspiring English sources

Exact(1)

In our work we attempted to design a sentiment combining function that, based on the sentiment of single words, provides the absolute sentiment of the message as a normalised value from the range of −100 to 100.

Similar(59)

Our goal was to analyse the negative sentiment of all the messages related to EDL that had been posted on Twitter prior to each of the four events mentioned in the previous sub-section.

Then, the messages were reprocessed and computed by sentiment algorithm; we can obtaine the sentiment values of the messages in different periods.

Using the 853 messages found in the network analysis, we perform a sentiment analysis of the messages to identify the opinions of e-cigarettes in the community.

The idea was that, for a given average sentiment of a message, the difference between the overall positive and overall negative sentiments should also depend on the number of positive and negative words in the message.

Illness slowed him down, yet the inclusion of "You're Goin' Miss Your Candyman", from his 1972 album What Color His Love, on the soundtrack of the film Intouchables last year demonstrated the timeless appeal of his music, and the lyric's sentiment fitted the message of tolerance in the French comedy-drama.

Once your data is submitted, it is processed to extract the sentiment of your message, which updates the DataCafe display to reflect those sentiments and the revenue generated by your data.

Through the application of a normalisation function the sentiment of a message is represented as a value from a range of −100 to 100.

Scroll through the many categories and pages of emoji to find one that matches the sentiment of your message!

It can be noticed that the accuracy increased when the sentiment normalisation had been applied, indicating that the normalization function expresses more accurately the intensity of the sentiment of messages in comparison to the sum function.

The authors demonstrated that the mere count of tweets mentioning a certain party reflects the election outcome, while the sentiment of Twitter messages closely corresponds to the offline political landscape.

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