Modules / Lectures


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noc20_cs32_assigment_11noc20_cs32_assigment_11
noc20_cs32_assigment_12noc20_cs32_assigment_12
noc20_cs32_assigment_13noc20_cs32_assigment_13
noc20_cs32_assigment_2noc20_cs32_assigment_2
noc20_cs32_assigment_3noc20_cs32_assigment_3
noc20_cs32_assigment_4noc20_cs32_assigment_4
noc20_cs32_assigment_5noc20_cs32_assigment_5
noc20_cs32_assigment_6noc20_cs32_assigment_6
noc20_cs32_assigment_7noc20_cs32_assigment_7
noc20_cs32_assigment_8noc20_cs32_assigment_8
noc20_cs32_assigment_9noc20_cs32_assigment_9


Sl.No Chapter Name MP4 Download
1IntroductionDownload
2Answer to the puzzleDownload
3Introduction to Python-1Download
4Introduction to Python-2Download
5Introduction to Networkx-1Download
6Introduction to Networkx-2Download
7Social Networks: The ChallengeDownload
8Google Page RankDownload
9Searching in a NetworkDownload
10Link PredictionDownload
11The ContagionsDownload
12Importance of AcquaintancesDownload
13Marketing on Social NetworksDownload
14Introduction to DatasetsDownload
15Ingredients NetworkDownload
16Synonymy NetworkDownload
17Web GraphDownload
18Social Network DatasetsDownload
19Datasets: Different Formats Download
20Datasets : How to Download?Download
21Datasets: Analysing Using NetworkxDownload
22Datasets: Analysing Using GephiDownload
23Introduction : Emergence of ConnectednessDownload
24Advanced Material : Emergence of ConnectednessDownload
25Programming Illustration : Emergence of ConnectednessDownload
26Summary to DatasetsDownload
27 Introduction Download
28Granovetter's Strength of weak tiesDownload
29Triads, clustering coefficient and neighborhood overlapDownload
30Structure of weak ties, bridges, and local bridgesDownload
31Validation of Granovetter's experiment using cell phone dataDownload
32EmbedednessDownload
33Structural HolesDownload
34Social CapitalDownload
35Finding Communities in a graph (Brute Force Method)Download
36Community Detection Using Girvan Newman AlgorithmDownload
37Visualising Communities using GephiDownload
38Tie Strength, Social Media and Passive EngagementDownload
39Betweenness Measures and Graph PartitioningDownload
40Strong and Weak Relationship - Summary Download
41Introduction to Homophily - Should you watch your company ?Download
42Selection and Social InfluenceDownload
43Interplay between Selection and Social InfluenceDownload
44Homophily - Definition and measurementDownload
45Foci Closure and Membership ClosureDownload
46Introduction to Fatman Evolutionary model Download
47Fatman Evolutionary Model- The Base Code (Adding people)Download
48Fatman Evolutionary Model- The Base Code (Adding Social Foci)Download
49Fatman Evolutionary Model- Implementing HomophilyDownload
50Quantifying the Effect of Triadic Closure Download
51Fatman Evolutionary Model- Implementing ClosuresDownload
52Fatman Evolutionary Model- Implementing Social InfluenceDownload
53Fatman Evolutionary Model- Storing and analyzing longitudnal dataDownload
54Spatial Segregation: An IntroductionDownload
55Spatial Segregation: Simulation of the Schelling Model Download
56Spatial Segregation: ConclusionDownload
57Schelling Model Implementation-1(Introduction)Download
58Schelling Model Implementation-2 (Base Code)Download
59Schelling Model Implementation-3 (Visualization and Getting a list of boundary and internal nodes)Download
60Schelling Model Implementation-4 (Getting a list of unsatisfied nodes)Download
61Schelling Model Implementation-5 (Shifting the unsatisfied nodes and visualizing the final graph)Download
62CHAPTER - 5 POSITIVE AND NEGATIVE RELATIONSHIPS (INTRODUCTION)Download
63STRUCTURAL BALANCEDownload
64ENEMY'S ENEMY IS A FRIENDDownload
65Characterizing the structure of balanced networksDownload
66BALANCE THEOREMDownload
67PROOF OF BALANCE THEOREMDownload
68Introduction to positive and negative edgesDownload
69Outline of implemantationDownload
70Creating graph, displaying it and counting unstable trianglesDownload
71Moving a network from an unstable to stable stateDownload
72Forming two coalitionsDownload
73Forming two coalitions contdDownload
74Visualizing coalitions and the evolutionDownload
75The Web GraphDownload
76Collecting the Web GraphDownload
77Equal Coin DistributionDownload
78Random Coin DroppingDownload
79Google Page Ranking Using Web GraphDownload
80Implementing PageRank Using Points Distribution Method-1Download
81Implementing PageRank Using Points Distribution Method-2Download
82Implementing PageRank Using Points Distribution Method-3Download
83Implementing PageRank Using Points Distribution Method-4Download
84Implementing PageRank Using Random Walk Method -1Download
85Implementing PageRank Using Random Walk Method -2Download
86DegreeRank versus PageRankDownload
87We FollowDownload
88Why do we Follow?Download
89Diffusion in NetworksDownload
90Modeling DiffusionDownload
91Modeling Diffusion (continued)Download
92Impact of Commmunities on DiffusionDownload
93Cascade and ClustersDownload
94Knowledge, Thresholds and the Collective ActionDownload
95An Introduction to the Programming Screencast (Coding 4 major ideas)Download
96The Base CodeDownload
97Coding the First Big Idea - Increasing the PayoffDownload
98Coding the Second Big Idea - Key PeopleDownload
99Coding the Third Big Idea- Impact of Communities on CascadesDownload
100Coding the Fourth Big Idea - Cascades and ClustersDownload
101Introduction to Hubs and Authorities (A Story)Download
102Principle of Repeated Improvement (A story)Download
103Principle of Repeated Improvement (An example)Download
104Hubs and AuthoritiesDownload
105PageRank Revisited - An exampleDownload
106PageRank Revisited - Convergence in the ExampleDownload
107PageRank Revisited - Conservation and ConvergenceDownload
108PageRank, conservation and convergence - Another exampleDownload
109Matrix Multiplication (Pre-requisite 1)Download
110Convergence in Repeated Matrix Multiplication (Pre-requisite 1)Download
111Addition of Two Vectors (Pre-requisite 2)Download
112Convergence in Repeated Matrix Multiplication- The DetailsDownload
113PageRank as a Matrix OperationDownload
114PageRank ExplainedDownload
115Introduction to PowerlawDownload
116Why do Normal Distributions Appear?Download
117Power Law emerges in WWW graphsDownload
118Detecting the Presence of PowerlawDownload
119Rich Get Richer PhenomenonDownload
120 Summary So FarDownload
121Implementing Rich-getting-richer Phenomenon (Barabasi-Albert Model)-1Download
122Implementing Rich-getting-richer Phenomenon (Barabasi-Albert Model)-2Download
123Implementing a Random Graph (Erdos- Renyi Model)-1Download
124Implementing a Random Graph (Erdos- Renyi Model)-2Download
125Forced Versus Random Removal of Nodes (Attack Survivability)Download
126Rich Get Richer - A Possible ReasonDownload
127Rich Get Richer - The Long TailDownload
128Epidemics- An IntroductionDownload
129Introduction to epidemics (contd..)Download
130Simple Branching Process for Modeling EpidemicsDownload
131Simple Branching Process for Modeling Epidemics (contd..)Download
132Basic Reproductive NumberDownload
133Modeling epidemics on complex networksDownload
134SIR and SIS spreading modelsDownload
135Comparison between SIR and SIS spreading modelsDownload
136Basic Reproductive Number Revisited for Complex NetworksDownload
137Percolation modelDownload
138Analysis of basic reproductive number in branching model (The problem statement)Download
139Analyzing basic reproductive number 2Download
140Analyzing basic reproductive number 3Download
141Analyzing basic reproductive number 4Download
142Analyzing basic reproductive number 5Download
143Small World Effect - An IntroductionDownload
144Milgram's ExperimentDownload
145The ReasonDownload
146The Generative ModelDownload
147Decentralized Search - IDownload
148Decentralized Search - IIDownload
149Decentralized Search - IIIDownload
150Programming illustration- Small world networks : IntroductionDownload
151Base codeDownload
152Making homophily based edgesDownload
153Adding weak tiesDownload
154Plotting change in diameterDownload
155Programming illustration- Myopic Search : IntroductionDownload
156Myopic SearchDownload
157Myopic Search comparision to optimal searchDownload
158Time Taken by Myopic SearchDownload
159PseudoCores : IntroductionDownload
160How to be ViralDownload
161Who are the right key nodes?Download
162finding the right key nodes (the core)Download
163Coding K-Shell DecompositionDownload
164Coding cascading ModelDownload
165Coding the importance of core nodes in cascadingDownload
166Pseudo coreDownload
167Live Session 1Download
168Live Session 2Download
169Live Session 3Download
170Live Session 4Download
171Live Session 5Download

Sl.No Chapter Name English
1IntroductionDownload
Verified
2Answer to the puzzleDownload
Verified
3Introduction to Python-1Download
Verified
4Introduction to Python-2Download
Verified
5Introduction to Networkx-1Download
Verified
6Introduction to Networkx-2Download
Verified
7Social Networks: The ChallengeDownload
Verified
8Google Page RankDownload
Verified
9Searching in a NetworkDownload
Verified
10Link PredictionDownload
Verified
11The ContagionsDownload
Verified
12Importance of AcquaintancesDownload
Verified
13Marketing on Social NetworksDownload
Verified
14Introduction to DatasetsDownload
Verified
15Ingredients NetworkDownload
Verified
16Synonymy NetworkDownload
Verified
17Web GraphDownload
Verified
18Social Network DatasetsDownload
Verified
19Datasets: Different Formats Download
Verified
20Datasets : How to Download?Download
Verified
21Datasets: Analysing Using NetworkxDownload
Verified
22Datasets: Analysing Using GephiDownload
Verified
23Introduction : Emergence of ConnectednessDownload
Verified
24Advanced Material : Emergence of ConnectednessDownload
Verified
25Programming Illustration : Emergence of ConnectednessDownload
Verified
26Summary to DatasetsDownload
Verified
27 Introduction Download
Verified
28Granovetter's Strength of weak tiesDownload
Verified
29Triads, clustering coefficient and neighborhood overlapDownload
Verified
30Structure of weak ties, bridges, and local bridgesDownload
Verified
31Validation of Granovetter's experiment using cell phone dataDownload
Verified
32EmbedednessDownload
Verified
33Structural HolesDownload
Verified
34Social CapitalDownload
Verified
35Finding Communities in a graph (Brute Force Method)Download
Verified
36Community Detection Using Girvan Newman AlgorithmDownload
Verified
37Visualising Communities using GephiDownload
Verified
38Tie Strength, Social Media and Passive EngagementDownload
Verified
39Betweenness Measures and Graph PartitioningDownload
Verified
40Strong and Weak Relationship - Summary Download
Verified
41Introduction to Homophily - Should you watch your company ?Download
Verified
42Selection and Social InfluenceDownload
Verified
43Interplay between Selection and Social InfluenceDownload
Verified
44Homophily - Definition and measurementDownload
Verified
45Foci Closure and Membership ClosureDownload
Verified
46Introduction to Fatman Evolutionary model Download
Verified
47Fatman Evolutionary Model- The Base Code (Adding people)Download
Verified
48Fatman Evolutionary Model- The Base Code (Adding Social Foci)Download
Verified
49Fatman Evolutionary Model- Implementing HomophilyDownload
Verified
50Quantifying the Effect of Triadic Closure Download
Verified
51Fatman Evolutionary Model- Implementing ClosuresDownload
Verified
52Fatman Evolutionary Model- Implementing Social InfluenceDownload
Verified
53Fatman Evolutionary Model- Storing and analyzing longitudnal dataDownload
Verified
54Spatial Segregation: An IntroductionDownload
Verified
55Spatial Segregation: Simulation of the Schelling Model Download
Verified
56Spatial Segregation: ConclusionDownload
Verified
57Schelling Model Implementation-1(Introduction)Download
Verified
58Schelling Model Implementation-2 (Base Code)Download
Verified
59Schelling Model Implementation-3 (Visualization and Getting a list of boundary and internal nodes)Download
Verified
60Schelling Model Implementation-4 (Getting a list of unsatisfied nodes)Download
Verified
61Schelling Model Implementation-5 (Shifting the unsatisfied nodes and visualizing the final graph)Download
Verified
62CHAPTER - 5 POSITIVE AND NEGATIVE RELATIONSHIPS (INTRODUCTION)Download
Verified
63STRUCTURAL BALANCEDownload
Verified
64ENEMY'S ENEMY IS A FRIENDDownload
Verified
65Characterizing the structure of balanced networksDownload
Verified
66BALANCE THEOREMDownload
Verified
67PROOF OF BALANCE THEOREMDownload
Verified
68Introduction to positive and negative edgesDownload
Verified
69Outline of implemantationDownload
Verified
70Creating graph, displaying it and counting unstable trianglesDownload
Verified
71Moving a network from an unstable to stable stateDownload
Verified
72Forming two coalitionsDownload
Verified
73Forming two coalitions contdDownload
Verified
74Visualizing coalitions and the evolutionDownload
Verified
75The Web GraphDownload
Verified
76Collecting the Web GraphDownload
Verified
77Equal Coin DistributionDownload
Verified
78Random Coin DroppingDownload
Verified
79Google Page Ranking Using Web GraphDownload
Verified
80Implementing PageRank Using Points Distribution Method-1Download
Verified
81Implementing PageRank Using Points Distribution Method-2Download
Verified
82Implementing PageRank Using Points Distribution Method-3Download
Verified
83Implementing PageRank Using Points Distribution Method-4Download
Verified
84Implementing PageRank Using Random Walk Method -1Download
Verified
85Implementing PageRank Using Random Walk Method -2Download
Verified
86DegreeRank versus PageRankDownload
Verified
87We FollowDownload
Verified
88Why do we Follow?Download
Verified
89Diffusion in NetworksDownload
Verified
90Modeling DiffusionDownload
Verified
91Modeling Diffusion (continued)Download
Verified
92Impact of Commmunities on DiffusionDownload
Verified
93Cascade and ClustersDownload
Verified
94Knowledge, Thresholds and the Collective ActionDownload
Verified
95An Introduction to the Programming Screencast (Coding 4 major ideas)Download
Verified
96The Base CodeDownload
Verified
97Coding the First Big Idea - Increasing the PayoffDownload
Verified
98Coding the Second Big Idea - Key PeopleDownload
Verified
99Coding the Third Big Idea- Impact of Communities on CascadesDownload
Verified
100Coding the Fourth Big Idea - Cascades and ClustersDownload
Verified
101Introduction to Hubs and Authorities (A Story)Download
Verified
102Principle of Repeated Improvement (A story)Download
Verified
103Principle of Repeated Improvement (An example)Download
Verified
104Hubs and AuthoritiesDownload
Verified
105PageRank Revisited - An exampleDownload
Verified
106PageRank Revisited - Convergence in the ExampleDownload
Verified
107PageRank Revisited - Conservation and ConvergenceDownload
Verified
108PageRank, conservation and convergence - Another exampleDownload
Verified
109Matrix Multiplication (Pre-requisite 1)Download
Verified
110Convergence in Repeated Matrix Multiplication (Pre-requisite 1)Download
Verified
111Addition of Two Vectors (Pre-requisite 2)Download
Verified
112Convergence in Repeated Matrix Multiplication- The DetailsDownload
Verified
113PageRank as a Matrix OperationDownload
Verified
114PageRank ExplainedDownload
Verified
115Introduction to PowerlawDownload
Verified
116Why do Normal Distributions Appear?Download
Verified
117Power Law emerges in WWW graphsDownload
Verified
118Detecting the Presence of PowerlawDownload
Verified
119Rich Get Richer PhenomenonDownload
Verified
120 Summary So FarDownload
Verified
121Implementing Rich-getting-richer Phenomenon (Barabasi-Albert Model)-1Download
Verified
122Implementing Rich-getting-richer Phenomenon (Barabasi-Albert Model)-2Download
Verified
123Implementing a Random Graph (Erdos- Renyi Model)-1Download
Verified
124Implementing a Random Graph (Erdos- Renyi Model)-2Download
Verified
125Forced Versus Random Removal of Nodes (Attack Survivability)Download
Verified
126Rich Get Richer - A Possible ReasonDownload
Verified
127Rich Get Richer - The Long TailDownload
Verified
128Epidemics- An IntroductionDownload
Verified
129Introduction to epidemics (contd..)Download
Verified
130Simple Branching Process for Modeling EpidemicsDownload
Verified
131Simple Branching Process for Modeling Epidemics (contd..)Download
Verified
132Basic Reproductive NumberDownload
Verified
133Modeling epidemics on complex networksDownload
Verified
134SIR and SIS spreading modelsDownload
Verified
135Comparison between SIR and SIS spreading modelsDownload
Verified
136Basic Reproductive Number Revisited for Complex NetworksDownload
Verified
137Percolation modelDownload
Verified
138Analysis of basic reproductive number in branching model (The problem statement)Download
Verified
139Analyzing basic reproductive number 2Download
Verified
140Analyzing basic reproductive number 3Download
Verified
141Analyzing basic reproductive number 4Download
Verified
142Analyzing basic reproductive number 5Download
Verified
143Small World Effect - An IntroductionDownload
Verified
144Milgram's ExperimentDownload
Verified
145The ReasonDownload
Verified
146The Generative ModelDownload
Verified
147Decentralized Search - IDownload
Verified
148Decentralized Search - IIDownload
Verified
149Decentralized Search - IIIDownload
Verified
150Programming illustration- Small world networks : IntroductionDownload
Verified
151Base codeDownload
Verified
152Making homophily based edgesDownload
Verified
153Adding weak tiesDownload
Verified
154Plotting change in diameterDownload
Verified
155Programming illustration- Myopic Search : IntroductionDownload
Verified
156Myopic SearchDownload
Verified
157Myopic Search comparision to optimal searchDownload
Verified
158Time Taken by Myopic SearchDownload
Verified
159PseudoCores : IntroductionDownload
Verified
160How to be ViralDownload
Verified
161Who are the right key nodes?Download
Verified
162finding the right key nodes (the core)Download
Verified
163Coding K-Shell DecompositionDownload
Verified
164Coding cascading ModelDownload
Verified
165Coding the importance of core nodes in cascadingDownload
Verified
166Pseudo coreDownload
Verified
167Live Session 1PDF unavailable
168Live Session 2PDF unavailable
169Live Session 3PDF unavailable
170Live Session 4PDF unavailable
171Live Session 5PDF unavailable


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2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
9TeluguNot Available