AKTU Social Media Analytics and Data Analysis (BCAM061) Question Paper 2025-26

Note: Attempt all Sections. In case of any missing data; choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 7 = 14 marks

1. What is a sociogram?
2. Mention the applications of social media analytics in business.
3. Define path and connectivity in a graph.
4. What is a node in a social network?
5. How does homophily influence social network formation?
6. Differentiate between descriptive and predictive modeling.
7. Mention the role of natural language processing in sentiment and trend analysis.

Section B

Q2. Attempt any three of the following · 7 × 3 = 21 marks

1. Describe the social media landscape and classify different types of social networks with suitable examples.
2. Explain adjacency matrices and discuss how graphs are used to represent social networks.
3. Discuss affiliation networks and citation networks and compare their characteristics.
4. Explain Facebook analytics and discuss key metrics such as demographics, reach, and engagement.
5. What is clickstream analysis? Explain A/B testing and analyze its role in optimizing user engagement and conversions.

Section C

Q3

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain the concept of social media analytics and discuss its need and applications in small and large organizations.
2. Explain various social media business models and their applications in different domains.

Q4

Attempt any one part of the following · 7 × 1 = 7 marks

1. What is a weighted network? Compare random graphs, weighted networks, and hypergraphs with suitable examples.
2. Explain adjacency matrices and discuss how graphs are used to represent social networks.

Q5

Attempt any one part of the following · 7 × 1 = 7 marks

1. What is clustering in networks? Describe snowball sampling, contact tracing, and random walks in network data collection.
2. What is a biological network? Explain how network concepts are applied in bioinformatics.

Q6

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain social contexts such as affiliation, identity, and social capital in social network analysis.
2. Explain the working of Google Website Optimizer and its role in website experimentation.

Q7

Attempt any one part of the following · 7 × 1 = 7 marks

1. What is data visualization? Discuss influence maximization and link prediction and their applications in marketing and recommendation systems.
2. Discuss and compare web crawling and indexing and explain their importance in large-scale data collection.

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