<s>[INST] Sentiment Analysis is a popular NLP (Natural Language Processing) technique for detecting whether a sentence or a piece of text expresses a positive or negative sentiment. There are many real-world use cases for Sentiment Analysis, which include but are not limited to social media monitoring, feedback analysis, and emotion detection. Sentiment Analysis is also often used in understanding public opinion on various social issues and political events. In this question, you will implement the VADER sentiment lexicon for Text Analysis. The VADER (Valence Aware Dictionary and sEntiment Reasoner) is a popular model used for Sentiment Analysis. The VADER lexicon consists of words with their sentiment scores. The objective is to compute the sentiment score of a piece of text using the baseline SentimentIntensity scores obtained from the VADER lexicon. The total sentiment scores range from -1 (extreme negative sentiment) to 1 (extreme positive sentiment). A score of zero signifies a neutral sentiment. In this question, we will be using the NLTK library, specifically the nltk.sentiment module in Python.[/INST]