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Introduction | Tweet Sentiment Analysis
Tweet Sentiment Analysis
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Course Content

Tweet Sentiment Analysis

bookIntroduction

Sentiment analysis, also known as opinion mining, is the use of natural language processing, text analysis, and computational linguistics to identify and extract subjective information from source materials. This technique is commonly used to determine the attitudes, opinions, and emotions of a speaker or writer with respect to some topic or the overall contextual polarity of a document.

Sentiment analysis can be used to classify the sentiment of text into positive, negative, or neutral categories, or to identify subjective information in source materials such as social media posts, reviews, and survey responses. It is widely used in fields such as marketing, customer service, and politics to gain insights and track public opinion.

For this project we will use a dataset coming from twitter and we will try to classify the tweets according to their sentiment.

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Sentiment analysis, also known as opinion mining, is the use of natural language processing, text analysis, and computational linguistics to identify and extract subjective information from source materials. This technique is commonly used to determine the attitudes, opinions, and emotions of a speaker or writer with respect to some topic or the overall contextual polarity of a document.

Sentiment analysis can be used to classify the sentiment of text into positive, negative, or neutral categories, or to identify subjective information in source materials such as social media posts, reviews, and survey responses. It is widely used in fields such as marketing, customer service, and politics to gain insights and track public opinion.

For this project we will use a dataset coming from twitter and we will try to classify the tweets according to their sentiment.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 1. Chapter 1
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