Social Media Data Analytics
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 resea
Monthly Subscription Starting at AED 99 + VAT
- Level Professional
- المدة 13 ساعات hours
- الطبع بواسطة University of Washington
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Offered by
عن
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.الوحدات
Lesson
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4
Videos
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2
Assignment
2
Assignment
- Quiz-1
- Quiz-2
4
Videos
- Video-1: Introduction
- Video-2: Structured vs. Unstructured Data
- Video-3: Analyzing Structured Data
- Video-4: Visualization of Data
Installations and configurations
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4
Readings
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1
Discussion
1
Discussions
- Installation and Configuration of Development Environment
4
Readings
- Anaconda Installation
- Python installation, configuration, and usage
- R installation
- R/RStudio Setup Guide (on Windows)
Introduction
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1
Videos
1
Videos
- Video-1: Introduction
Python
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1
Videos
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3
Readings
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1
Assignment
1
Assignment
- Python Programming Exercise
1
Videos
- Video-2: Introduction to Python Programming
3
Readings
- Errata: please read this first
- Python Packages Installation
- (Optional) Introduction to Python for Econometrics, Statistics and Data Analysis
Twitter data collection with Python
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1
Videos
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2
Readings
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1
PeerReview
1
Peer Review
- Twitter data download using Python
1
Videos
- Video-3: Using Python to Extract Data from Twitter
2
Readings
- Script: twitter_search.py
- Twitter libraries
YouTube data collection with Python
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1
Videos
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1
Readings
-
1
Assignment
1
Assignment
- YouTube data download using Python
1
Videos
- Video-4: Using Python to Extract Data from YouTube
1
Readings
- Script: youtube_search.py
Introduction
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1
Videos
1
Videos
- Video-1: Introduction
Analyzing Twitter data using Python
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1
Videos
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1
Readings
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1
Discussion
-
1
Assignment
1
Assignment
- Statistical Analysis with Twitter Data
1
Discussions
- Statistical Analysis with Twitter Data
1
Videos
- Video-2: Analyzing Social Media Data Using Python
1
Readings
- Script: twitter_process.py
R
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1
Videos
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4
Readings
1
Videos
- Video-3: Introduction to R
4
Readings
- Data: iqsize.csv
- R Installation Guide
- Installing R Packages
- Statistical Analysis with R
Data analytics with R
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1
Videos
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3
Readings
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1
Discussion
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1
PeerReview
1
Peer Review
- Data Visualization using R
1
Discussions
- Data Visualization using R
1
Videos
- Video-4: Social Media Data Analysis with R
3
Readings
- Read this first
- Scripts for converting json to csv
- Data Visualization with ggplot2 (R) - Cheat Sheet
Introduction
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1
Videos
1
Videos
- Video-1: Introduction
Case study-1
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1
Videos
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2
Readings
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1
Discussion
-
1
Assignment
1
Assignment
- Sentiment Analysis with Twitter
1
Discussions
- Sentiment Analysis with Twitter Data
1
Videos
- Video-2: Sentiment Analysis with Twitter Data
2
Readings
- Script: twitter_sentiments.py
- NLTK
Case study-2
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1
Videos
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2
Readings
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1
PeerReview
1
Peer Review
- Text Mining with Twitter
1
Videos
- Video-3: Text Mining of Twitter Data
2
Readings
- Script: text_mining_twitter.r
- An Introduction to Network Analysis with R and statnet
Conclusion
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1
Videos
1
Videos
- Video-4: Conclusion
Auto Summary
"Social Media Data Analytics" is an advanced course designed for professionals in Big Data and Analytics. Taught by Dr. Chirag Shah, this course empowers learners to collect, process, and analyze social media data from platforms like YouTube, Twitter, and Flickr. Participants will master techniques such as correlation, regression, classification, and sentiment analysis. Ideal for roles like Social Media Analyst and Data Analyst, the course includes practical assignments and projects. Offered by Coursera, this 780-minute course is available with a Starter subscription, perfect for data analysts looking to expand into social media analytics.
Chirag Shah