sentiment.self.drive.csv

The dataset Twitter comments on self-driving cars A balanced dataset with 2385 tweets labeled as positive, neutral or negative. The tweets are related to the theme self-driving cars. The CSV file has the following fields: Tweed ID: sequential identifier for every single document (tweet); Sentiment: every tweet is labeled as positive, neutral or negative; . Text: the tweeted text. The methods Naive method (40 points]: using the lexicons in R (affin, bing, ncr) classify each tweet sentiment. Show the results using precision, recall, and F1. Explain why the method's performance was good or bad The dataset Twitter comments on self-driving cars A balanced dataset with 2385 tweets labeled as positive, neutral or negative. The tweets are related to the theme self-driving cars. The CSV file has the following fields: Tweed ID: sequential identifier for every single document (tweet); Sentiment: every tweet is labeled as positive, neutral or negative; . Text: the tweeted text. The methods Naive method (40 points]: using the lexicons in R (affin, bing, ncr) classify each tweet sentiment. Show the results using precision, recall, and F1. Explain why the method's performance was good or bad