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What are the current approaches for analyzing emotions within a piece of text? Which tools and Python packages should you use for sentiment analysis? This week, Jodie Burchell, developer advocate for data science at JetBrains, returns to the show to discuss modern sentiment analysis in Python.
Jodie holds a PhD in clinical psychology. We discuss how her interest in studying emotions has continued throughout her career.
In this episode, Jodie covers three ways to approach sentiment analysis. We start by discussing traditional lexicon-based and machine-learning approaches. Then, we dive into how specific types of LLMs can be used for the task. We also share multiple resources so you can continue to explore sentiment analysis on your own.
This week’s episode is brought to you by Sentry.
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Topics:
00:00:00 – Introduction 00:02:31 – Conference talks in 2024 00:04:23 – Background on sentiment analysis and studying feelings 00:07:09 – What led you to study emotions? 00:08:57 – Dimensional emotion classification 00:10:42 – Different types of sentiment analysis 00:14:28 – Lexicon-based approaches 00:17:50 – VADER - Valence Aware Dictionary and sEntiment Reasoner 00:19:41 – TextBlob and subjectivity scoring 00:21:48 – Sponsor: Sentry 00:22:52 – Measuring sentiment of New Year’s resolutions 00:27:28 – Lexicon-based approaches links for experimenting 00:28:35 – Multiple language support in lexicon-based packages 00:35:23 – Machine learning techniques 00:39:20 – Tools for this approach 00:42:54 – Video Course Spotlight 00:44:15 – Advantages to the machine learning models approach 00:45:55 – Large language model approach 00:48:44 – Encoder vs decoder models 00:52:09 – Comparing the concept of fine-tuning 00:56:49 – Is this a recent development? 00:58:08 – Ways to practice with these techniques 01:00:10 – Do you find this to be a promising approach? 01:07:45 – Resources to practice with all the techniques 01:11:06 – Upcoming conference talks 01:11:56 – Thanks and goodbyeShow Links:
Introduction to Sentiment Analysis in Python - The PyCharm Blog How to Do Sentiment Analysis With Large Language Models - The PyCharm Blog Talks - Jodie Burchell: Lies, damned lies and large language models - YouTube Mirror, mirror: LLMs and the illusion of humanity - Jodie Burchell - YouTube Separating fact from fiction in a world of AI fairytales - Jodie Burchell - NDC London 2024 - YouTube Hurt Feelings (Rap Version) - Flight Of The Conchords (Lyrics) - YouTube Universal Emotions - What are Emotions? - Paul Ekman Group VADER - nltk.sentiment.vader module clips/pattern: Web mining module for Python, with tools for scraping, natural language processing, machine learning TextBlob: Simplified Text Processing — TextBlob documentation Power vs. Force: The Hidden Determinants of Human Behavior by David R. Hawkins - Goodreads Episode #36: Sentiment Analysis, Fourier Transforms, and More Python Data Science – The Real Python Podcast Use Sentiment Analysis With Python to Classify Movie Reviews – Real Python Sentiment Analysis: First Steps With Python’s NLTK Library – Real Python Sentiment Analysis in DataSpell with @JetBrainsTV - YouTube Episode #119: Natural Language Processing and How ML Models Understand Text – The Real Python Podcast spaCy - Industrial-strength Natural Language Processing in Python amazon_polarity - Datasets at Hugging Face Introduction to Sentiment Analysis in Python - The PyCharm Blog Kaggle: Your Machine Learning and Data Science Community ZS BIT AI Community Day - 10 December 2024 Jodie Burchell - The JetBrains Blog Jodie Burchell’s Blog - Standard error Jodie Burchell 🇦🇺🇩🇪 (@t_redactyl) - Twitter Jodie Burchell (@t-redactyl.bsky.social) — Bluesky Jodie Burchell 🇦🇺🇩🇪 (@t_redactyl@fosstodon.org) - Fosstodon JetBrains: Essential tools for software developers and teamsLevel up your Python skills with our expert-led courses:
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