This project focuses on analyzing social networks within a university class, aiming to uncover patterns of interactions and collaboration among peers and professors. The goal is to gain insights into academic and social dynamics within the university setting.
Inspired by the concept of "six degrees of separation," this project analyzes the social network within a university class to explore how closely connected individuals are, both to each other and to professors. Through data collection, graph representation, and the application of Dijkstra's algorithm, the project uncovers key insights into academic and social interactions, providing a foundation for future research and improvements in academic support systems.
- Data Collection: Gathered data through Google Forms, where students rated their connections with classmates and professors on a scale of 1 to 10.
- Graph Construction: Developed a weighted, directed graph using C++ to represent the social network.
- Algorithm Implementation: Applied Dijkstra's algorithm to find the shortest paths between nodes, identifying the proximity and connectivity among individuals.
- Analysis and Insights: Identified influential nodes, examined collaboration patterns, and explored professor-student connections.
- Discovered significant correlations between connection strengths and academic performance.
- Uncovered clusters of students with strong connections, indicating potential study circles.
- Provided insights for enhancing academic support systems and fostering community within the class.
src.cpp: Contains the C++ source code for graph construction and Dijkstra's algorithm.Social_Network_Analysis_Responses.csv: Includes sample data collected from the class.include: Includes necessary csv-parsed library.
Special thanks to Prof. Zobia Rehman for her invaluable guidance throughout this project. Gratitude to my project group members: Eman Rizwan, Malaika Sattar, and Syeda Aleeza Tahir for their collaboration and support. Thanks to all the students who participated in the data collection process.
Contributions are welcome! Please create a pull request or open an issue to discuss your ideas.