Byte-Sized-Chunks: Sentiment Analysis

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 989 MB

Genre: eLearning | Language: English

Use Python and the Twitter API to build your own sentiment analyzer!

Sentiment Analysis (or) Opinion Mining is a field of NLP that deals with extracting subjective information (positive/negative, like/dislike, emotions).

Learn why it's useful and how to approach the problem: Both Rule-Based and ML-Based approaches.

The details are really important - training data and feature extraction are critical. Sentiment Lexicons provide us with lists of words in different sentiment categories that we can use for building our feature set.

All this is in the run up to a serious project to perform Twitter Sentiment Analysis. We'll spend some time on Regular Expressions which are pretty handy to know as we'll see in our code-along.

Sentiment Analysis:

Why it's useful,

Approaches to solving - Rule-Based , ML-Based

Training & Feature Extraction

Sentiment Lexicons

Regular Expressions

Twitter API

Sentiment Analysis of Tweets with Python