Generic Opinion Mining (English)
A generic sentiment analysis pipeline for English text. The pipeline identifies sentences containing basic positive and negative opinions, and includes basic entity detection. It creates an annotation for every opinionated sentence, with features denoting:
- the polarity of the opinion (positive or negative)
- a score denoting the opinion strength
- a broad classification of the emotion expressed by the sentence
- an optional reference to the entity acting as the target of the opinion
- a feature denoting presence of sarcasm
- linguistic features such as whether the sentence is a question, conditional, imperative etc.
It also averages the sentiment over the whole document and provides an indication of standard deviation.
The pipeline is designed for use on good quality longer texts such as news articles or reviews.
|Sentiment:Sentence||Sentences, with the following additional features:
|Sentiment:SentenceSentiment||Opinionated sentences, with features polarity (positive or negative) and score (from +1 to -1), plus sarcasm with value "yes" or "no" for sentences that are identified as sarcastic or not. There is also a feature emotion giving a broad classification of the emotion expressed by the sentence, possible values are "cute", "happy", "bad", "anger", "disgust", "fear" or "sadness".|
|Sentiment:SentenceSet||An average sentiment score across the set of sentences in the document, with features polarity and score for the mean score, and score_std_dev for the standard deviation of the individual sentence scores. A low standard deviation indicates that the opinionated sentences in this document all express similar opinions, a higher value indicates a wider variety of sentiments across the document.|
|Additional annotations available if selected|
|Sentiment:Person||Named entities as detected by ANNIE|
|Sentiment:SentimentTarget||The target of a sentiment expression, with polarity, score and sarcasm features as described above.|
Use this pipeline
You can process up to 1,200 documents per day free of charge using the REST API, at an average rate of 2 documents/sec. Higher quotas are available for research users by arrangement, contact us for details.
The API endpoint for this pipeline is:
You can process any amount of data with this pipeline on a pay-as-you-go basis, for £0.80 per hour. This can be data you upload yourself, data you collected from Twitter, or the results of a previous job.