Social Media Data Analytics: Insights from Online Platforms
Master techniques to collect, analyze, and visualize social media data using Python and R for actionable insights.
Master techniques to collect, analyze, and visualize social media data using Python and R for actionable insights.
This intermediate-level course equips learners with practical skills to harness the power of social media data analytics. Over four modules, you'll learn to collect data from platforms like Twitter, YouTube, and Flickr using APIs, process structured and unstructured data, perform statistical analyses, and conduct sentiment analysis. The course covers both Python and R programming, teaching you to use these tools for data collection, analysis, and visualization. You'll gain hands-on experience through mini-projects involving real social media data, preparing you for roles such as Social Media Analyst or Data Analyst. By the end of the course, you'll be able to build a comprehensive workflow for leveraging social media data in marketing, public relations, and business intelligence.
4.1
(293 ratings)
44,639 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Utilize API services to collect data from social media platforms like Twitter, YouTube, and Flickr
Process structured data using correlation, regression, and classification methods
Analyze unstructured data, primarily text, for sentiment analysis
Use Python and R for data collection, analysis, and visualization
Apply statistical techniques to derive insights from social media data
Create effective data visualizations to present findings
Skills you'll gain
This course includes:
3.5 Hours PreRecorded video
6 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course on Social Media Data Analytics provides learners with practical skills to collect, analyze, and visualize data from various social media platforms. The curriculum covers four main areas: introduction to data analytics, data collection techniques, data analysis and visualization, and real-world case studies. Students will learn to use Python and R for extracting data from Twitter and YouTube, perform statistical analyses, create visualizations, and conduct sentiment analysis and text mining. The course emphasizes hands-on learning through mini-projects and assignments, preparing students for roles in social media analysis, web analytics, and marketing intelligence.
Introduction to Data Analytics
Module 1 · 2 Hours to complete
Collecting and Extracting Social Media Data
Module 2 · 3 Hours to complete
Data Analysis, Visualization, and Exploration
Module 3 · 3 Hours to complete
Case Studies
Module 4 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Expert in Information Seeking and Human-Computer Interaction
Chirag Shah is an Associate Professor at the University of Washington's Information School (iSchool) and the Founding Director of the InfoSeeking Lab. His research focuses on information seeking, human-computer interaction (HCI), and social media, supported by significant grants from agencies such as the National Science Foundation (NSF) and the National Institute of Health (NIH). Shah's work involves interactive information retrieval, recommender systems, and machine learning techniques, utilizing both lab and field user studies.
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4.1 course rating
293 ratings
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