SMA PYQ 2025-26 AKTU Question Paper

AKTU · BTECH · Semester 6 · Social Media Analytics and Data Analysis · Session 2025-26 · PYQ

AKTU Social Media Analytics and Data Analysis previous year question paper 2025-26 for B.Tech Semester 6. Covers Introduction to Social Media, Graphs and…

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Social Media Analytics and Data Analysis AKTU syllabus

  1. Unit 1: Introduction to Social Media
  2. Unit 2: Graphs and Matrices
  3. Unit 3: Network Fundamentals
  4. Unit 4: Social Network and Modelling
  5. Unit 5: Processing and Visualizing Social Media Data

Questions in Social Media Analytics and Data Analysis AKTU PYQ 2025-26

  1. Q1a. What is a sociogram? (2 marks, 2025-26)
  2. Q1b. Mention the applications of social media analytics in business. (2 marks, 2025-26)
  3. Q1c. Define path and connectivity in a graph. (2 marks, 2025-26)
  4. Q1d. What is a node in a social network? (2 marks, 2025-26)
  5. Q1e. How does homophily influence social network formation? (2 marks, 2025-26)
  6. Q1f. Differentiate between descriptive and predictive modeling. (2 marks, 2025-26)
  7. Q1g. Mention the role of natural language processing in sentiment and trend analysis. (2 marks, 2025-26)
  8. Q2a. Describe the social media landscape and classify different types of social networks with suitable examples. (7 marks, 2025-26)
  9. Q2b. Explain adjacency matrices and discuss how graphs are used to represent social networks. (7 marks, 2025-26)
  10. Q2c. Discuss affiliation networks and citation networks and compare their characteristics. (7 marks, 2025-26)
  11. Q2d. Explain Facebook analytics and discuss key metrics such as demographics, reach, and engagement. (7 marks, 2025-26)
  12. Q2e. What is clickstream analysis? Explain A/B testing and analyze its role in optimizing user engagement and conversions. (7 marks, 2025-26)
  13. Q3a. Explain the concept of social media analytics and discuss its need and applications in small and large organizations. (7 marks, 2025-26)
  14. Q3b. Explain various social media business models and their applications in different domains. (7 marks, 2025-26)
  15. Q4a. What is a weighted network? Compare random graphs, weighted networks, and hypergraphs with suitable examples. (7 marks, 2025-26)
  16. Q4b. Explain adjacency matrices and discuss how graphs are used to represent social networks. (7 marks, 2025-26)
  17. Q5a. What is clustering in networks? Describe snowball sampling, contact tracing, and random walks in network data collection. (7 marks, 2025-26)
  18. Q5b. What is a biological network? Explain how network concepts are applied in bioinformatics. (7 marks, 2025-26)
  19. Q6a. Explain social contexts such as affiliation, identity, and social capital in social network analysis. (7 marks, 2025-26)
  20. Q6b. Explain the working of Google Website Optimizer and its role in website experimentation. (7 marks, 2025-26)
  21. Q7a. What is data visualization? Discuss influence maximization and link prediction and their applications in marketing and recommendation systems. (7 marks, 2025-26)
  22. Q7b. Discuss and compare web crawling and indexing and explain their importance in large-scale data collection. (7 marks, 2025-26)

AKTU paper codes: BCAM061

Social Media Analytics and Data Analysis previous year papers

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