<prompt> Unda programu ambayo inachambua hisia za makala.  <response>: Certainly! Heres a simple program in Python that can help you analyze the sentiment of articles:pythonimport nltkfrom nltk.sentiment import SentimentIntensityAnalyzer Instantiate the sentiment analyzersia SentimentIntensityAnalyzerdef analyze_sentimentarticle: Analyze the sentiment of an article. :param article: string The article text to be analyzed :return: float, float, float The compound sentiment score, positive sentiment score, and negative sentiment score for the article. Tokenize the article into sentences sentences nltk.sent_tokenizearticle Initialize variables to store sentiment scores compound_scores positive_scores negative_scores Iterate over sentences and generate sentiment scores for sentence in sentences: sentiment sia.polarity_scoressentence compound_scores.appendsentimentcompound positive_scores.appendsentimentpos negative_scores.appendsentimentneg Calculate average sentiment scores avg_compound_score sumcompound_scores lencompound_scores avg_positive_score sumpositive_scores lenpositive_scores avg_negative_score sumnegative_scores lennegative_scores return avg_compound_score, avg_positive_score, avg_negative_score Example usagearticle Artificial intelligence AI is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. Leading AI textbooks define the field as the study of intelligent agents: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. AI research is interdisciplinary and subsumes fields as diverse as mathematics, statistics, computer science, psychology, neuroscience and many others. compound, positive, negative analyze_sentimentarticleprintfCompound Score: compound, Positive Score: positive, Negative Score: negativeThis program uses the sentiment analyzer from the nltk library to analyze the sentiment of an article. The function analyze_sentiment takes an article in string format as an input and returns the average compound, positive, and negative sentiment scores for the article.Note that this program requires the nltk library to be installed, and the nltk.sentiment.vader_lexicon resource to be downloaded. You 