EE 6605 Learning Project Assignment Objective: Work through one learning project 1) Search literature 2) Conceive a new topic 3) Establish a new model or propose a new method (describe the algorithm or procedure, perhaps derive an analytic formula, e.g., distribution) 4) Carry out some simulations and plot simulation figures / tables 5) Analyze the observations from simulation results with comparisons 6) Conclude the investigation Requirement: Must be related to complex networks Apply some learned network knowledge Not anything from degree work (thesis/publications) Object Report: Write one learning project report 1) Title 2) Abstract 3) Introduction (background information) 4) Problem formulation (motivation) 5) Model or Method description 6) Simulation (set-up, parameters, results, plots, tables) using any program software or language (MatLab, C++, Python,…) 7) Analysis and/or comparisons 8) Conclusions 9) References 10) Appendix (optional, e.g., program codes or method proof) Requirement: 10±2 one-sided pages, typed (in Word or latex) pdf Example: Facebook network modeling The Facebook Network o The largest online social network in the world (2.9 billion active users in 2022) o Two data sets in 2014, with fully connected components of 63731 and 72261577 users respectively o 99.91% of users are located in a single large connected component Review of Existing Models: o Scale-Free (BA) model o Distance Social Network (DSN) model o Asymmetric Weights Dynamic (AWD) model o Exponential Random Graph models o Markov Random (MR) model o Random Triangle (RT) model Background Henneberg Model Original Model L. Henneberg (1911) Modified Henneberg Model Node Addition Edge Rewiring Modified Model with Edge Rewiring Idea: Something new (or different) Simulations + Plots Small size Large size > 500 Reasonable size: 50 < N < 500 o BA (Scale-Free) model o DSN: Distance Social Network model o AWD: Asymmetric Weights Dynamic model o Exponential Random Graph models o MR: Markov Random model o RT: Random Triangle model Simulation + Plots Power-Law (before taking log-log) Simulation + Plots Small size Larger size (After taking log-log) AD: Average Distance APL: Average Path Length ACC: Average Clustering Coefficient Simulation Results and Comparison Real Data Not required But if so, a plus A real Facebook dataset: 72,261,577 users (too big for this project to do) Observations and Analysis Observations: 1. Power-law degree distribution 2. Small-world features 3. Community structure 4. Hierarchical structure Analysis: 1. Why power-law Because … 2. Why small-world Because … 3. Why community structure Because … 4. Why hierarchical structure Because … Conclusions and Discussions Conclusions: 1. … 2. … 3. … Discussions: 1. Limitation … 2. Future work … References and Appendix References [1] G. Chen, Lecture Nodes, EE6605, CityU, 2022 [2] L. Henneberg, Die graphische Statik der starren Systeme, Leipzig, 1911 [3] ... Appendix (Optional) Program Codes Final Report: 1) Title [and Name, ID#, 1/2 p] 2) Abstract [1/2 p] 3) Introduction [1~2 pp] 4) Problem formulation [1 p] 5) Model description [1~2 p] 6) Simulation [3~5 pp, including figures/tables] 7) Analysis [2~3 pp] 8) Conclusions [1/2 p] 9) References [1/2 p] 10) Appendix [< 2 pp] 10±2 one-sided pages, typed (in Word or latex) 1.5-line spacing, 12-point font size pdf file to upload to Canvas You may do something else in similar quality and quantity Project Report is due to Canvas Anytime before midnight Wednesday 30 November 2022 Late Reports will not be accepted Be serious and Enjoy
