Artificial Intelligence in Social Media Analytics
Master AI techniques for social media analysis: machine learning, NLP, sentiment analysis, and topic modeling for actionable digital insights.
Master AI techniques for social media analysis: machine learning, NLP, sentiment analysis, and topic modeling for actionable digital insights.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Social Media Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
English
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What you'll learn
Define and evaluate machine learning classifiers for effective data analysis
Process and parse social media text data using NLP techniques
Conduct sentiment analysis on social media content to gauge public opinion
Apply topic modeling to extract themes from social media conversations
Build semantic networks for advanced social media analysis
Skills you'll gain
This course includes:
3.35 Hours PreRecorded video
12 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course explores the intersection of artificial intelligence and social media analytics, equipping learners with essential skills to analyze digital landscapes. The curriculum covers machine learning fundamentals, natural language processing, sentiment analysis, and topic modeling, providing hands-on experience with real-world social media data. Students learn to construct classifiers, perform sentiment analysis, and build semantic networks, all while developing practical skills in applying AI techniques to uncover patterns and insights from social media content.
Course Introduction
Module 1 · 14 Minutes to complete
Machine Learning
Module 2 · 4 Hours to complete
Natural Language Processing
Module 3 · 4 Hours to complete
Sentiment Analysis
Module 4 · 4 Hours to complete
Topic Modeling
Module 5 · 4 Hours to complete
Fee Structure
Instructor
Pioneering Social Network Analysis and AI at Johns Hopkins University
Dr. Ian McCulloh is an esteemed associate professor at Johns Hopkins University, holding joint appointments in the Bloomberg School of Public Health and the Whiting School of Engineering. His research focuses on social neuroscience, social network analysis, and the application of artificial intelligence to enhance understanding of online influence and strategic communication. With over 100 peer-reviewed publications and several influential books, including Social Network Analysis with Applications and ISIS in Iraq: Understanding the Social and Psychological Foundations of Terror, Dr. McCulloh has established himself as a leading voice in his field. He also founded the Brain Rise Foundation, a nonprofit dedicated to advancing neuroscience research for substance abuse recovery. Prior to his academic career, he had a distinguished military service, retiring as a Lieutenant Colonel after 20 years, during which he led innovative projects in data-driven social science research for countering extremism. Dr. McCulloh's multifaceted expertise and commitment to applying science for societal benefit make him a valuable asset to both academia and public health initiatives.
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Frequently asked questions
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