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Social Media Analytics and Data Analysis (BCAM061) AKTU previous year questions 2025

Every Social Media Analytics and Data Analysis question from 1 AKTU papers, tagged by unit, topic and marks. A few recent questions from each unit are listed below; open the page to filter by unit, topic or mark type.

Unit 1: Introduction to Social Media – AKTU PYQs

  • Define Social Media Analytics (SMA) and explain its primary objective. (2 marks, 2025, Social Media Introduction)
  • Compare between Small and Large organizations in terms of Social Media Analytics (SMA) application. (2 marks, 2025, SMA in Organisations)
  • 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, 2025, SMA in Organisations)
  • 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, 2025, Types of Social Networks)
  • 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, 2025, Business Models and Web Search)

Unit 2: Graphs and Matrices – AKTU PYQs

  • What is an adjacency matrix, and how is it used to represent a graph? (2 marks, 2025, Graph Theory Basics)
  • Define the concept of "distance" in a graph and explain its significance in graph theory. (2 marks, 2025, Graph Theory Basics)
  • 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, 2025, Random Graphs and Network Evolution)
  • 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, 2025, Graph Theory Basics)
  • 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, 2025, Nodes Ties and Influencers)

Unit 3: Network Fundamentals – AKTU PYQs

  • With help of an example prove the importance of equivalence in network structures? (2 marks, 2025, Network Structures)
  • 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, 2025, Special Network Types)
  • 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, 2025, Network Structures)
  • Discuss the process of snowball sampling and its application in network studies. How does it compare to random walks in network sampling? (7 marks, 2025, Contact Tracing and Random Walks)

Unit 4: Social Network and Modelling – AKTU PYQs

  • What is the concept of "structural holes" in social network theory and how does it influence network connectivity? (2 marks, 2025, Social Contexts and Capital)
  • 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, 2025, Google Analytics)
  • 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, 2025, Predictive and Descriptive Modelling)
  • 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, 2025, Social Contexts and Capital)

Unit 5: Processing and Visualizing Social Media Data – AKTU PYQs

  • What is Influence Maximization in social networks, and why is it important for viral marketing strategies? (2 marks, 2025, Processing and Visualizing Data)
  • 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, 2025, Processing and Visualizing Data)
  • 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, 2025, Web Data Analytics Methods)
  • 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, 2025, NLP for Micro-text Analysis)