aspect based sentiment analysis

absa.py

# pip install git+https://github.com/ScalaConsultants/Aspect-Based-Sentiment-Analysis

import aspect_based_sentiment_analysis as absa

nlp = absa.load()
text = ("We are great fans of Slack, but we wish the subscriptions "
        "were more accessible to small startups.")

slack, price = nlp(text, aspects=['slack', 'price'])
print(slack.sentiment, slack.sentiment.value)
print(price.sentiment, price.sentiment.value)


####
#Sentiment.positive 2
#Sentiment.negative 1

absa.summary(price)

#Sentiment.negative for "price"
#Scores (neutral/negative/positive): [0.012 0.958 0.0]


def generate_absa(text: str, foods: List[str]) -> List[Dict]:
    absa_list = []
    aspects = nlp(text, aspects=list(foods))
    for food in foods:
        absa_dict = {}
        sentiment = aspects[food].sentiment
        absa_dict['food'] = food
        absa_dict['sentiment_name'] = sentiment.name
        absa_dict['sentiment_value'] = sentiment.value
        absa_list.append(absa_dict)
    return absa_list