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Online Social Media -
Developer's Perspective
Summer Workshop @ IGDTUW
Tech Support by PreCog@IIITD
Network Analysis
anupama_agg
anupama_agg
PhD Student @ IIITD
Advisor: Dr. PK
Research Area:
Computational Social Science
Data Scientist
Interned at UMBC, USA &
UFMG, Brazil
DSSG in India
anupama_agg
PhD Student @ IIITD
Advisor: Dr. PK
Research Area:
Computational Social Science
Data Scientist
Interned at UMBC, USA &
UFMG, Brazil
DSSG in India
anupama_agg
PhD Student @ IIITD
Advisor: Dr. PK
Research Area:
Computational Social Science
Data Scientist
Interned at UMBC, USA &
UFMG, Brazil
DSSG in India
anupama_agg
PhD Student @ IIITD
Advisor: Dr. PK
Research Area:
Computational Social Science
Data Scientist
Interned at UMBC, USA &
UFMG, Brazil
DSSG in India
anupama_agg
PhD Student @ IIITD
Advisor: Dr. PK
Research Area:
Computational Social Science
Data Scientist
Interned at UMBC, USA &
UFMG, Brazil
DSSG in India
anupama_agg
PhD Student @ IIITD
Advisor: Dr. PK
Research Area:
Computational Social Science
Data Scientist
Interned at UMBC, USA &
UFMG, Brazil
DSSG in India
anupama_agg
2:00 pm
3:00 pm
4:00 pm
4:30 pm
5:00 pm
Social Network Analysis (SNA)
•SNA Metrics
•Centrality, Modularity, Communities,
Indegree, Outdegree, Homophily…
•Get your own Twitter Data
•Data Analysis - Gephi
Brainstorming Activity
Q&A / Help in Research(!)
Get Your Twitter Data!
•Twecoll : Command Line Twitter Data Collection Tool
•Friends (Followees), Friends of Friends
http://bit.ly/IGDTUWAA
> python twecoll init twitter_username
> python twecoll fetch twitter_username
> python twecoll edgelist twitter_username
> cat anupama_agg.gml | grep -v weight |
grep - v rank > anupama_agg_no_rank.gml
What’s a Graph?
Nodes: Entities (like Users)
Edges: Kind of Relationships
How would a Computer understand a Graph?
???
How would a Computer understand a Graph?
Adjacency Matrix
GraphML
CSV
Adjacency Matrix
src: http://www.stoimen.com/blog/2012/08/31/computer-algorithms-graphs-and-their-representation/
GraphML Format
src: http://graphml.graphdrawing.org/primer/graphml-primer.html
SNA Metrics
src: http://www.slideshare.net/ganith2k13/graph-theory-26101317
SNA Metrics
Centrality : Finding out which is the most
central / important node
src: https://www.cl.cam.ac.uk/teaching/1213/L109/stna-lecture3.pdf
Indegree: Most influential
Outdegree: Who disseminates information
Betweenness: Quickly approachable
Closeness: Who is close to everyone
SNA Metrics
Community : Group of similar people
Modularity : Fraction of the edges that fall
within the given group
Communities based
on Degree
2:00 pm
3:00 pm
4:00 pm
4:30 pm
5:00 pm
Social Network Analysis (SNA)
•SNA Metrics
•Centrality, Modularity, Communities,
Indegree, Outdegree, Homophily…
•Get your own Twitter Data
•Data Analysis - Gephi
Brainstorming Activity
Q&A / Help in Research(!)
2:00 pm
3:00 pm
4:00 pm
4:30 pm
5:00 pm
Social Network Analysis (SNA)
•SNA Metrics
•Centrality, Modularity, Communities,
Indegree, Outdegree, Homophily…
•Get your own Twitter Data
•Data Analysis - Gephi
Brainstorming Activity
Q&A / Help in Research(!)
Find Food
Enthusiasts!
Aim / Phenomena to Study:
Find Food Enthusiasts
Social Network:
Instagram
Kind of Network Data Needed:
Users of photos tagged #foodporn
Who likes whose photos
What will I get?
Users who post best food photos (Indegree Centrality / Ranking)
Users who like food (photos) a lot! (Outdegree Centrality / Ranking)
2:00 pm
3:00 pm
4:00 pm
4:30 pm
5:00 pm
Social Network Analysis (SNA)
•SNA Metrics
•Centrality, Modularity, Communities,
Indegree, Outdegree, Homophily…
•Get your own Twitter Data
•Data Analysis - Gephi
Brainstorming Activity
Q&A / Help in Research(!)
“Who Followed You” TimeStamp Data
https://github.com/rickshawman/twitter
Email generated file to
anupamaa@iiitd.ac.in

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IGDTUW workshop

  • 1. Online Social Media - Developer's Perspective Summer Workshop @ IGDTUW Tech Support by PreCog@IIITD Network Analysis
  • 4. PhD Student @ IIITD Advisor: Dr. PK Research Area: Computational Social Science Data Scientist Interned at UMBC, USA & UFMG, Brazil DSSG in India anupama_agg
  • 5. PhD Student @ IIITD Advisor: Dr. PK Research Area: Computational Social Science Data Scientist Interned at UMBC, USA & UFMG, Brazil DSSG in India anupama_agg
  • 6. PhD Student @ IIITD Advisor: Dr. PK Research Area: Computational Social Science Data Scientist Interned at UMBC, USA & UFMG, Brazil DSSG in India anupama_agg
  • 7. PhD Student @ IIITD Advisor: Dr. PK Research Area: Computational Social Science Data Scientist Interned at UMBC, USA & UFMG, Brazil DSSG in India anupama_agg
  • 8. PhD Student @ IIITD Advisor: Dr. PK Research Area: Computational Social Science Data Scientist Interned at UMBC, USA & UFMG, Brazil DSSG in India anupama_agg
  • 9. PhD Student @ IIITD Advisor: Dr. PK Research Area: Computational Social Science Data Scientist Interned at UMBC, USA & UFMG, Brazil DSSG in India anupama_agg
  • 10. 2:00 pm 3:00 pm 4:00 pm 4:30 pm 5:00 pm Social Network Analysis (SNA) •SNA Metrics •Centrality, Modularity, Communities, Indegree, Outdegree, Homophily… •Get your own Twitter Data •Data Analysis - Gephi Brainstorming Activity Q&A / Help in Research(!)
  • 11. Get Your Twitter Data! •Twecoll : Command Line Twitter Data Collection Tool •Friends (Followees), Friends of Friends http://bit.ly/IGDTUWAA > python twecoll init twitter_username > python twecoll fetch twitter_username > python twecoll edgelist twitter_username > cat anupama_agg.gml | grep -v weight | grep - v rank > anupama_agg_no_rank.gml
  • 12. What’s a Graph? Nodes: Entities (like Users) Edges: Kind of Relationships
  • 13. How would a Computer understand a Graph? ???
  • 14. How would a Computer understand a Graph? Adjacency Matrix GraphML CSV
  • 18. SNA Metrics Centrality : Finding out which is the most central / important node src: https://www.cl.cam.ac.uk/teaching/1213/L109/stna-lecture3.pdf Indegree: Most influential Outdegree: Who disseminates information Betweenness: Quickly approachable Closeness: Who is close to everyone
  • 19. SNA Metrics Community : Group of similar people Modularity : Fraction of the edges that fall within the given group Communities based on Degree
  • 20. 2:00 pm 3:00 pm 4:00 pm 4:30 pm 5:00 pm Social Network Analysis (SNA) •SNA Metrics •Centrality, Modularity, Communities, Indegree, Outdegree, Homophily… •Get your own Twitter Data •Data Analysis - Gephi Brainstorming Activity Q&A / Help in Research(!)
  • 21. 2:00 pm 3:00 pm 4:00 pm 4:30 pm 5:00 pm Social Network Analysis (SNA) •SNA Metrics •Centrality, Modularity, Communities, Indegree, Outdegree, Homophily… •Get your own Twitter Data •Data Analysis - Gephi Brainstorming Activity Q&A / Help in Research(!)
  • 23.
  • 24. Aim / Phenomena to Study: Find Food Enthusiasts Social Network: Instagram Kind of Network Data Needed: Users of photos tagged #foodporn Who likes whose photos What will I get? Users who post best food photos (Indegree Centrality / Ranking) Users who like food (photos) a lot! (Outdegree Centrality / Ranking)
  • 25. 2:00 pm 3:00 pm 4:00 pm 4:30 pm 5:00 pm Social Network Analysis (SNA) •SNA Metrics •Centrality, Modularity, Communities, Indegree, Outdegree, Homophily… •Get your own Twitter Data •Data Analysis - Gephi Brainstorming Activity Q&A / Help in Research(!)
  • 26. “Who Followed You” TimeStamp Data https://github.com/rickshawman/twitter Email generated file to anupamaa@iiitd.ac.in