The FriendLinker project focuses on identifying indirect composite relations within an ego network, specifically exploring the Friend relationship to uncover connections between different egos.
The algorithm in this project facilitates the discovery of friend connections within a defined limit (L). The results vary based on the chosen limit:
- If L = 1 => Result: Direct Friends (1st Connection)
- If L = 2 => Result: Friends of Friends (2nd Connection)
- If L = 3 => Result: Friends of Friends of Friends (3rd Connection), and so forth...
The project's outcome helps visualize the relationships among egos within the network based on the specified connection limits.
- Understand the basic framework of the dataset
- Implement the algorithm on the dataset
- Publish applicable results through graphs with appropriate parameters
- Develop a user-friendly interface displaying the traversal of each node and the algorithm's progress
To utilize FriendLinker:
- Input the ego network dataset.
- Set the desired limit (L) to determine the level of indirect friendship relations.
- Run the algorithm to uncover and visualize the connections.
- Use the provided UI to navigate through nodes and observe the algorithm's progression.
This project is licensed under the MIT License. See the LICENSE file for details.
The FriendLinker project is authored by MANAI MORTADHA. Contact: [mannaimortadha898@gmail.com].
For inquiries or feedback, contact [mannaimortadha898@gmail.com].
If you find this project helpful and wish to support its development:
- Sponsor Link: You can sponsor this project [here].
- Buy Me a Coffee: [Link to Buy Coffeehttps://github.com/sponsors/MortadhaMannai/sponsorships?sponsor=MortadhaMannai&tier_id=328439&preview=false]: If you'd like, you can also buy me a coffee as a token of appreciation.