Performance Study of N-grams in the Analysis of Sentiments

In this work, a study investigation was carried out using n-grams to classify sentiments with different machine learning and deep methods. We used approach, which combines existing techniques, the problem of predicting sequence tags understand advantages problems confronted unigrams, bigrams trigrams analyse economic texts. Our aims fill gap by evaluating performance these features on texts in domain nine sentiment analysis techniques found more insights. show that comparing datasets multiple we extracted useful intelligence. The evaluation involves assessing precision, recall, f1-score accuracy function output several algorithms proposed. methods were tested Amazon, IMDB, Reuters, Yelp review our comprehensive experiment shows effectiveness sentiments.