Byte-Sized-Chunks: Sentiment Analysis
MP4 | Video: AVC 1280×720 | 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
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