SMA PYQ 2024-25 AKTU Question Paper

AKTU · BTECH · Semester 6 · Social Media Analytics and Data Analysis · Session 2024-25 · PYQ

AKTU Social Media Analytics and Data Analysis previous year question paper 2024-25 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 2024-25

  1. Q1a. Define Social Media Analytics (SMA) and explain its primary objective. (2 marks, 2024-25)
  2. Q1b. What is an adjacency matrix, and how is it used to represent a graph? (2 marks, 2024-25)
  3. Q1c. With help of an example prove the importance of equivalence in network structures? (2 marks, 2024-25)
  4. Q1d. What is the concept of "structural holes" in social network theory and how does it influence network connectivity? (2 marks, 2024-25)
  5. Q1e. What is Influence Maximization in social networks, and why is it important for viral marketing strategies? (2 marks, 2024-25)
  6. Q1f. Compare between Small and Large organizations in terms of Social Media Analytics (SMA) application. (2 marks, 2024-25)
  7. Q1g. Define the concept of "distance" in a graph and explain its significance in graph theory. (2 marks, 2024-25)
  8. Q2a. Discuss the role and significance of Social Media Analytics in both small and large organizations. How do the needs and strategies differ across different scales? (7 marks, 2024-25)
  9. Q2b. Describe random graphs and network evolution. What are some key models used to represent random graph generation and how does the network evolve over time? (7 marks, 2024-25)
  10. Q2c. Describe the concept of citation networks and explain their role in academic research. How do citation networks evolve, and what are their characteristics in terms of connectivity and structure? (7 marks, 2024-25)
  11. Q2d. Evaluate the use of Google Analytics for analyzing website performance. Discuss its key implementation technologies, limitations, and privacy concerns. How does Google Website Optimizer enhance the performance analysis of a website? (7 marks, 2024-25)
  12. Q2e. Explain the concept of Collective Classification in network data. How does it differ from traditional classification methods, and what are its applications in social network analysis? (7 marks, 2024-25)
  13. Q3a. Explain the different types of social networks (e.g., user-generated content, affiliation) and discuss how each can be used for marketing and business analysis. Provide examples from popular social media platforms. (7 marks, 2024-25)
  14. Q3b. Describe the basics of Web Search Engines and Digital Advertising. How do these technologies interact with Social Media to enhance business models and marketing strategies? (7 marks, 2024-25)
  15. Q4a. Discuss the process and significance of Breadth-First Search (BFS) in graph traversal. How can BFS be used to determine connectivity in a graph? (7 marks, 2024-25)
  16. Q4b. 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? (7 marks, 2024-25)
  17. Q5a. Explain the concept of clustering in networks. How do clustering coefficients help in understanding network structures? Provide real-life examples of clustering in social or biological networks. (7 marks, 2024-25)
  18. Q5b. Discuss the process of snowball sampling and its application in network studies. How does it compare to random walks in network sampling? (7 marks, 2024-25)
  19. Q6a. Discuss the key differences between predictive and descriptive modeling in the context of social networks. Provide examples of each and explain their significance in understanding social behaviors. (7 marks, 2024-25)
  20. Q6b. Explain the concept of structural balance in social networks. How does it apply to understanding relationships within a network? Discuss how structural balance can be useful in identifying community dynamics or conflicts. (7 marks, 2024-25)
  21. Q7a. Describe the process of A/B testing in online advertising. How can it be used to optimize user experience and improve conversion rates? Discuss the challenges and limitations of A/B testing in a real-world context. (7 marks, 2024-25)
  22. Q7b. 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? (7 marks, 2024-25)

AKTU paper codes: BCAM061

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