University of Washington - Social Media Data Analytics
4.0 /5- Offered byCoursera
Social Media Data Analytics at Coursera Overview
Duration | 13 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Social Media Data Analytics at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 13 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Social Media Data Analytics at Coursera Course details
- Learner Outcomes: After taking this course, you will be able to:
- - Utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr.
- - Process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data.
- - Analyze unstructured data - primarily textual comments - for sentiments expressed in them.
- - Use different tools for collecting, analyzing, and exploring social media data for research and development purposes.
- Sample Learner Story: Data analyst wanting to leverage social media data.
- Isabella is a Data Analyst working as a consultant for a multinational corporation. She has experience working with Web analysis tools as well as marketing data. She wants to now expand into social media arena, trying to leverage the vast amounts of data available through various social media channels. Specifically, she wants to see how their clients, partners, and competitors view their products/services and talk about them. She hopes to build a new workflow of data analytics that incorporates traditional data processing using Web and marketing tools, as well as newer methods of using social media data.
- Sample Job Roles requiring these skills:
- - Social Media Analyst
- - Web Analyst
- - Data Analyst
- - Marketing and Public Relations
- Final Project Deliverable/ Artifact: The course will have a series of small assignments or mini-projects that involve data collection, analysis, and presentation involving various social media sources using the techniques learned in the class.
- The course was developed by Dr. Chirag Shah while he was a faculty member at Rutgers University. He is currently a faculty member at University of Washington.
Social Media Data Analytics at Coursera Curriculum
Introduction to Data Analytics
Video-1: Introduction
Video-2: Structured vs. Unstructured Data
Video-3: Analyzing Structured Data
Video-4: Visualization of Data
Anaconda Installation
Python installation, configuration, and usage
R installation
R/RStudio Setup Guide (on Windows)
Quiz-1
Quiz-2
Collecting and Extracting Social Media Data
Video-1: Introduction
Video-2: Introduction to Python Programming
Video-3: Using Python to Extract Data from Twitter
Video-4: Using Python to Extract Data from YouTube
Errata: please read this first
Python Packages Installation
(Optional) Introduction to Python for Econometrics, Statistics and Data Analysis
Script: twitter_search.py
Twitter libraries
Script: youtube_search.py
Python Programming Exercise
YouTube data download using Python
Data Analysis, Visualization, and Exploration
Video-1: Introduction
Video-2: Analyzing Social Media Data Using Python
Video-3: Introduction to R
Video-4: Social Media Data Analysis with R
Script: twitter_process.py
Data: iqsize.csv
R Installation Guide
Installing R Packages
Statistical Analysis with R
Read this first
Scripts for converting json to csv
Data Visualization with ggplot2 (R) - Cheat Sheet
Statistical Analysis with Twitter Data
Case Studies
Video-1: Introduction
Video-2: Sentiment Analysis with Twitter Data
Video-3: Text Mining of Twitter Data
Video-4: Conclusion
Script: twitter_sentiments.py
NLTK
Script: text_mining_twitter.r
An Introduction to Network Analysis with R and statnet
Sentiment Analysis with Twitter
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