SentimentAnalyzer.py
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import argparse
from google.cloud import language_v1
def print_result(annotations):
score = annotations.document_sentiment.score
magnitude = annotations.document_sentiment.magnitude
tot = 0
positive = 0
negative = 0
neutral = 0
for index, sentence in enumerate(annotations.sentences):
sentence_sentiment = sentence.sentiment.score
if sentence_sentiment > 0:
positive += 1
elif sentence_sentiment < 0:
negative += 1
else:
neutral += 1
# print(
# "Sentence {} has a sentiment score of {}".format(index, sentence_sentiment)
# )
tot += 1
print(
"Overall Sentiment: score of {} with magnitude of {}".format(score, magnitude)
)
return tot, positive, negative
def analyze(movie_review_filename):
client = language_v1.LanguageServiceClient()
with open(movie_review_filename, "r", encoding='utf-8-sig') as review_file:
# Instantiates a plain text document.
content = review_file.read()
document = language_v1.Document(content=content, type_=language_v1.Document.Type.PLAIN_TEXT)
annotations = client.analyze_sentiment(request={'document': document})
print_result(annotations)
if __name__ == "__main__":
analyze("data.txt")