Sentiment-Analysis-using-a-Lexicon-Approach for low resource language

Prerequisites • Python 3.x • Required Python packages: csv, pandas

Installation No specific installation steps are required. Ensure that you have the necessary Python packages installed.

Usage Here's an example of how to use the provided code: python

Load the lexicon

lexicon = load_lexicon('sentiment_lexicon.csv')

Load test data

with open('test_tweets.csv', 'r') as test_file: reader = csv.reader(test_file) data = [['tweet'], ['Polarity']] for row in reader: MyPolarity = ' ' tweet = row[0] MyPolarity = analyze_sentiment(row[0], lexicon) data.append([row[0], MyPolarity])

Create a DataFrame

annotatedtweets = pd.DataFrame(data, columns=['tweet', 'Polarity'])

Save the DataFrame to a CSV file

annotatedtweets.to_csv('my_annotated_tweets.csv')

Ensure that the lexicon file ('sentiment_lexicon.csv') and the test tweets file ('test_tweets.csv') are present in the current directory or provide the correct paths to the respective files.