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Semester 4ECM4401E-Commerce

Social Media Analytics (ECM4401) crash course, Online MBA, Semester 4:

This subject covers how businesses use social platforms like Twitter, Facebook, LinkedIn and Google+, and how to collect and analyse their data through APIs,…

  • 23 video lessons
  • 5h 6m
  • Study notes
  • 115 quiz questions
  • Assignment
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Social Media Analytics crash course

23 lessons in Social Media Analytics

Each lesson pairs one topic with a hand-picked video, trimmed to the part that teaches it.

About this subject

This subject covers how businesses use social platforms like Twitter, Facebook, LinkedIn and Google+, and how to collect and analyse their data through APIs, text mining, clustering and web scraping. After it, you will be able to extract social and web data, run frequency, similarity and TF-IDF analyses, and turn the results into insights for marketing decisions.

  1. 1

    Social Media Platforms and Their Features

    Module I, Introduction: Introduction to various social network platforms - Twitter, Facebook, Google+, LinkedIn and their features

    SOCIAL MEDIA ,TYPES, FEATURES and USES/ 6 Major social media platforms explained ...· THE MIND GYM· 12 min

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  2. 2

    Using Social Media to Promote Your Business

    Module I, Introduction: Utilizing social media for Business, Promoting business on social media

    How to Do Organic Social Media Marketing Strategically for Business in 2025 | Ashutosh Kumar· Ashutosh Kumar· 12 min

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  3. 3

    Twitter API Basics and Terminology

    Module II, Mining Twitter: Introduction to Twitter, Exploring Twitter's API and Terminology

    Twitter Marketing – Terminology· TutorialsPoint· 7 min

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  4. 4

    Trending Topics and Keyword Search on Twitter

    Module II, Mining Twitter: Exploring trending topics, Searching for keywords

    How To Check What’s Trending On Twitter/X (Easy Guide)· Guides by Leo· 1 min

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  5. 5

    Tweet Entities, Frequency Analysis and Diversity

    Module II, Mining Twitter: Extracting tweet entities with frequency analysis, Computing tweet diversity

    From Words to Wisdom - Text Analytics Use Cases· Knime· 3 min

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  6. 6

    Retweet Patterns and Histograms

    Module II, Mining Twitter: Examining patterns in retweets, Visualizing frequency data with histograms

    StatQuest: Histograms, Clearly Explained· StatQuest with Josh Starmer· 3 min

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  7. 7

    Facebook Social Graph API and Open Graph Protocol

    Module III, Mining Facebook & LinkedIn: Introduction, Understanding the Social Graph API, The Open Graph Protocol

    The Open Graph Protocol - Why And How You Should Use it On Your Website· ProgrammingPercy· 10 min

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  8. 8

    Analyzing Facebook Connections, Pages and Friendships

    Module III, Mining Facebook & LinkedIn: Analyzing Social Graph Connections, Analyzing facebook pages, Examining friendships

    📊 Understand Your Facebook Page Analytics to Get More Audience Engagement on Your Page Posts· Juhli Selby - Sandhi Social Marketing Training· 22 min

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  9. 9

    LinkedIn API Requests and Data Normalization

    Module III, Mining Facebook & LinkedIn: Introduction, Making LinkedIn API Requests, Normalizing data for analysis

    All you need to know about APIs | Product Management | PM School· PM School by NextLeap· 18 min

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  10. 10

    Data Clustering and Similarity Measures

    Module III, Mining Facebook & LinkedIn: Data Clustering, Measuring similarity, Clustering algorithms

    Lec - 23 : Clustering in Data Mining Explained | Top Clustering Methods You MUST Know!· Gate Smashers· 6 min

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  11. 11

    Google+ API Introduction

    Module IV, Mining Google+: Introduction, Exploring the Google+ API

    Mining data on Google+ with Python: 1- Setting up Google+ API with Python· The Luminary Coach - Sukhvinder Singh· 10 min

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  12. 12

    TF-IDF Explained

    Module IV, Mining Google+: Term Frequency, Inverse Document Frequency, Querying Human Language Data with TF-IDF

    Natural Language Processing|TF-IDF Intuition| Text Prerocessing· Krish Naik· 8 min

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  13. 13

    NLTK and Applying TF-IDF to Text

    Module IV, Mining Google+: Introducing the Natural Language Toolkit, Applying TF-IDF to Human Language, Finding Similar Documents

    Term Frequency Inverse Document Frequency TFIDF Cosine Similarity Solved Example Vidya Mahesh Huddar· Mahesh Huddar· 8 min

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  14. 14

    Bigram Analysis in Text

    Module IV, Mining Google+: Analyzing Bigrams in Human Language, Reflections on Analyzing Human Language Data

    Text Representation Using Bag Of n-grams: NLP Tutorial For Beginners - S2 E5· codebasics· 17 min

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  15. 15

    Web Scraping, Parsing and Crawling

    Module V, Mining Web pages: Scraping, Parsing, and Crawling the Web, Breadth-First Search in Web Crawling

    Ultimate Web Scraping tutorial· CodeWithHarry· 38 min

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  16. 16

    NLP Step by Step and Sentence Detection

    Module V, Mining Web pages: Discovering Semantics by Decoding Syntax, Natural Language Processing Illustrated Step-by-Step, Sentence Detection in Human Language Data

    Natural Language Processing In 10 Minutes | NLP Tutorial For Beginners | NLP Training | Simplilearn· Simplilearn· 7 min

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  17. 17

    Document Summarization

    Module V, Mining Web pages: Document Summarization

    Summarization in Natural Language Processing· Perfect Computer Engineer· 3 min

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  18. 18

    Entity-Centric Analysis and Text Analytics Quality

    Module V, Mining Web pages: Entity-Centric Analysis: A Paradigm Shift, Gisting Human Language Data, Quality of Analytics for Processing Human Language Data

    What is NLP (Natural Language Processing)?· IBM Technology· 10 min

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  19. 19

    Trending Topics, Tweet Search and Time-Series Data

    Module VI, Twitter Cookbook: Discovering the Trending Topics, Searching for Tweets, Collecting Time-Series Data

    Mining Twitter with Python : 1 - Hashtags, Topics, and Time Series· The Luminary Coach - Sukhvinder Singh· 12 min

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  20. 20

    Tweet Entities and Popular Tweets Analysis

    Module VI, Twitter Cookbook: Extracting Tweet Entities, Finding the Most Popular Tweets in a Collection of Tweets, Tabulating Frequency Analysis, Extracting Tweet Entities from Arbitrary Text

    Mining Twitter with Python : 5 - Analyzing tweets - entity analysis· The Luminary Coach - Sukhvinder Singh· 13 min

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  21. 21

    Retweeters and Retweet Attribution

    Module VI, Twitter Cookbook: Finding Users Who Have Retweeted a Status, Extracting a Retweet's Attribution

    Twitter Analysis: How to rank a user's influence· sentdex· 7 min

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  22. 22

    Robust Twitter Requests and User Profiles

    Module VI, Twitter Cookbook: Making Robust Twitter Request, Resolving User Profile Information, Harvesting a User's Tweets

    REST API Design Like a Senior Engineer (REST, GraphQL, Networking, Pagination, Auth, Security)· System Design Lab· 20 min

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  23. 23

    Friends, Followers and Friendship Graphs

    Module VI, Twitter Cookbook: Getting All Friends or Followers for a User, Analyzing a User's Friends and Followers, Crawling a Friendship Graph

    M3. Pt. 1 - Graphs in Social Media [IS735]· Cody Buntain· 59 min

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Assignment

Social Media Analytics Mini-Audit: From Platform Strategy to Text and Network Insights

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What you get

Less scrolling. More passing.

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    Hand-picked video lessons

    23 short lessons, each with the best YouTube explanation we could find, trimmed to the part that matters.

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    Study notes

    23 lessons come with a summary, key points, key terms and takeaways for quick revision.

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    Quizzes

    115 questions across the course, with the right answer and why, the moment you pick.

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    Assignments

    1 subject assignments with clear tasks, so you practise what each subject actually asks of you.

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    Notebook

    Write notes beside the video, stamped with the exact time, and jump back to that moment later.

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    Progress that follows you

    Completed lessons, quiz scores and where you stopped, saved to your account on every device.

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    Live chat

    A members-only live chat beside every lesson: doubts, tips, stickers and GIFs with your batch. One ₹19 pass opens every live chat.

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The Online MBA live chat. Study together, live.

A live chat right beside the video, shared by everyone studying Online MBA. Ask a Social Media Analytics doubt mid-lesson, share a shortcut, celebrate a finished semester.

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  • One live chat for all of Online MBA
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  • One ₹19 pass opens every live chat
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More from Online MBA Semester 4

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Social Media Analytics: common questions

This subject covers how businesses use social platforms like Twitter, Facebook, LinkedIn and Google+, and how to collect and analyse their data through APIs, text mining, clustering and web scraping. After it, you will be able to extract social and web data, run frequency, similarity and TF-IDF analyses, and turn the results into insights for marketing decisions. It's the Social Media Analytics subject of Online MBA, Semester 4, in 23 lessons: Social Media Platforms and Their Features; Using Social Media to Promote Your Business; Twitter API Basics and Terminology; Trending Topics and Keyword Search on Twitter; Tweet Entities, Frequency Analysis and Diversity; Retweet Patterns and Histograms; Facebook Social Graph API and Open Graph Protocol; Analyzing Facebook Connections, Pages and Friendships; LinkedIn API Requests and Data Normalization; Data Clustering and Similarity Measures; Google+ API Introduction; TF-IDF Explained; NLTK and Applying TF-IDF to Text; Bigram Analysis in Text; Web Scraping, Parsing and Crawling; NLP Step by Step and Sentence Detection; Document Summarization; Entity-Centric Analysis and Text Analytics Quality; Trending Topics, Tweet Search and Time-Series Data; Tweet Entities and Popular Tweets Analysis; Retweeters and Retweet Attribution; Robust Twitter Requests and User Profiles; Friends, Followers and Friendship Graphs.

Yes. Every video lesson is free to watch without an account. A free login unlocks study notes, quizzes, the assignment, a notebook and progress that syncs across devices.

About 5h 6m of video across 23 lessons, plus time for notes and quizzes. Go at your own pace; your place is saved.

Yes: “Social Media Analytics Mini-Audit: From Platform Strategy to Text and Network Insights”. It comes after the last lesson, with a brief, clear tasks and how the work is judged.

A members-only live chat beside the video, shared by everyone studying Online MBA, where learners ask doubts, share tips and react with stickers and GIFs. One ₹19 pass, paid once from your InsideEdge wallet, opens the live chat for every degree.

No. It's a crash course to help you understand and revise the subject quickly. Use it alongside your official study material and assignments.

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