Home › AKTU PYQ › Social Media Analytics and Data Analysis › Predicted Paper

Social Media Analytics and Data Analysis (BCAM061) AKTU predicted paper 2026-27

AI-predicted paper for Social Media Analytics and Data Analysis based on 1 past papers (2025). NOT an official AKTU paper. Use as a revision tool only.

Paper pattern

  • Section A: Attempt all questions. (14 marks)
  • Section B: Attempt any THREE questions out of five. (21 marks)
  • Section C: Attempt ONE question from each pair (a or b). (35 marks)

Why these questions

  • Unit 1 (Introduction to Social Media) dominates — 21% avg weightage
  • Asked every year: Social Media Introduction, SMA in Organisations
  • Low priority (never asked): SMA in Different Platforms, Weighted Networks and Hypergraphs
  • Most repeated topic: Graph Theory Basics

Section A – 2-mark questions

  • Write a short note on Business Models and Web Search.
  • What is an adjacency matrix, and how is it used to represent a graph?
  • List and briefly explain Special Network Types.
  • Write a short note on Google Analytics.
  • Write a short note on NLP for Micro-text Analysis.
  • Define Social Media Analytics (SMA) and explain its primary objective.
  • Write a short note on Nodes Ties and Influencers.

Section B – sample questions

  • Discuss the process and significance of Breadth-First Search (BFS) in graph traversal. How can BFS be used to determine connectivity in a graph?
  • Explain the concept of link analysis in network datasets. How can nodes, ties, and influencers be analyzed to understand the structure of a social or communication network?
  • Discuss the role of Natural Language Processing (NLP) techniques in micro-text analysis on social media. How do NLP methods help in understanding trends, identifying social influencers, and analyzing opinion spread in social networks?