Sentiment analysis

The sentiments app extracts expressed sentiments from your documents, positive or negative, as well as a percentage of positives and negatives per document.

Names as well as pronouns like he or she are resolved, i.e. He is a nice person. will appear as John Smith is a nice person. in the results.

Results

SentimentsResults

interface SentimentsResults {
    locations: Location[];
    positive: number;
    negative: number;
}

with:

Location

interface Location {
  polarity: SentimentPolarity;
  text: string;
  begin_offset: number;
  end_offset: number;
  object?: string;
  adjective?: string;
  noun?: string;
  verb?: string;
  expression?: string;
}

with:

SentimentPolarity

type SentimentPolarity = 'positive' | 'negative';

Examples

Sentiment analysis

The sentiments app extracts expressed sentiments from your documents, positive or negative, as well as a percentage of positives and negatives per document.

Names as well as pronouns like he or she are resolved, i.e. He is a nice person. will appear as John Smith is a nice person. in the results.

Results

SentimentsResults

interface SentimentsResults {
    locations: Location[];
    positive: number;
    negative: number;
}

with:

Location

interface Location {
  polarity: SentimentPolarity;
  text: string;
  begin_offset: number;
  end_offset: number;
  object?: string;
  adjective?: string;
  noun?: string;
  verb?: string;
  expression?: string;
}

with:

SentimentPolarity

type SentimentPolarity = 'positive' | 'negative';

API

Examples

You will need to install the english language module to run the sample. pip install wowool-english

Extracting sentiments

Note that in the results the sentiments have been resolved. For this to happen we need to add the entities in the pipeline.

from wowool.sdk import Pipeline
from wowool.sentiments.app_id import APP_ID

text = "John Dow is a very nice person, but he sucks at football."
pipeline = Pipeline(
    [
        "english",
        "entity",
        "sentiment",
        "sentiments.app",
    ]
)
document = pipeline(text)
print(document.results(APP_ID))

results:

{
    "positive": 50.0,
    "negative": 50.0,
    "locations": [
        {
            "polarity": "positive",
            "text": "John Dow is a very nice person",
            "begin_offset": 0,
            "end_offset": 30,
            "object": "John Dow",
            "adjective": "nice"
        },
        {
            "polarity": "negative",
            "text": "John Dow sucks",
            "begin_offset": 36,
            "end_offset": 44,
            "object": "John Dow",
            "expression": "suck",
            "comp": "intrans",
            "verb": "suck"
        }
    ]
}

License

In both cases you will need to acquirer a license file at https://www.wowool.com

Non-Commercial

This library is licensed under the GNU AGPLv3 for non-commercial use.  
For commercial use, a separate license must be purchased.  

Commercial license Terms

1. Grants the right to use this library in proprietary software.  
2. Requires a valid license key  
3. Redistribution in SaaS requires a commercial license.