课程: Hands-On Natural Language Processing

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Sentiment analysis with VADER

Sentiment analysis with VADER

课程: Hands-On Natural Language Processing

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Sentiment analysis with VADER

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- [Instructor] Let's practice how to do sentiment analysis with Valence Aware Dictionary and sEntiment Reasoner, VADER. At the end of the exercise, you will be able to calculate your own sentiment score and label them according to polarity. We'll be using the sentiment labeled sentences dataset from the open source UCI Machine Learning Repository and the Python library, VADER. First, download and unzip the dataset using the wget and unzip commands. Then combine the subsets of the dataset into a single data frame called df using pandas. Now, let's view information about the combined data frame using df.info and df itself. The output shows a total of 2,784 rows or reviews and their pre-labeled sentiment, where zero means negative and one means positive. Now, we can go ahead and generate the VADER sentiment score based on the review column. Looking at the data frame again, we can see we now have a new column named…

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