1. Demo: data input and transformation
Digital Humanities
Demo: data input and transformation

2. Data input for Gephi
Node and Edge tables
Presidential speech example

3. Two mode networks Affiliation or membership network
A set of actors, and a second set of events or activities to which the actors in the first set attend or belong.
Dyadic two-mode network
Relations in a two-mode network measure ties between the actors in one set and actors in a second set

4. Bipartite graph

5. Two mode data

6. Modality
A data set that contains information about two types of social entities (e.g. person and organizations) is a two mode network
Individuals, group, organization, community, institution, society
Think of individual persons as being embedded in networks that embedded in networks that are embedded in networks

7. Two-mode data For example: - - Participants of the same project
- Membership in the same organization
- Attendance at the same meetings
- Graduates of the same university
Heuristics/ rule of thumb, approximate
Given actor-by-event or actor-by-group data, we can always construct an actor-by-actor matrix by counting the number of events/groups that each pair of actors has in common. 

8. Affiliation Network
Putting context into the network by showing connections to activities, companies, organizations, neighborhoods, etc.
Bipartite graph: every edge joins two nodes belonging to different sets (actors vs. foci)
Sue
Bill
Chess Club
Band
Affiliations or foci

9. Two-mode affiliation network and its one –mode projection
Top row represents four teams and the bottom row represents the teams’
Members (e.g. co-authors on a paper or artists that make a show.
Teammates are members of a fully linked clique (e.g. ABC, BCD, CE, and DF)
Connections form between agents on separate teams when links like (BC) connect
The ABC, BCD, and CE teams.
Most social networks are conceived of as relations among a set of nodes, and therefore
represented as a 1-mode matrix (typically of 1s and 0s) or a simple graph or digraph. For
example, we might collect data on who is friendly with whom within an organization, or
who injects drugs with whom in a neighborhood.
However, 2-mode data are common in social network contexts as well. Typical examples
include, actor-by-event attendance (as in the DGG data), actor by group membership
(such as managers sitting on corporate boards), and actor by trait possession (such as
adjective checklist data), and actor by object possession (such as material style of life
scales in which inventories are made of household possessions).
In many cases when 2-mode data are collected, the analytical interest is focused on one
mode or the other. For example, in the DGG dataset, person-by-event attendances were
collected in order to understand social relations among the women, specifically, whether
women tended to have social relations primarily within their own social classes. In the
interlocking directorate literature, membership of executives on corporate boards is
collected mainly in order to understand how corporations are intertwined, and how the
structure of this connectivity affects corporate control of society.
However, it can also occur that neither mode dominates our analytical focus and the
primary interest is in the correspondence of one mode to the other. For example, a
university might ask its faculty which courses they prefer to teach. Here, the objective is
typically not to understand how faculty are related to each other through courses, nor how
courses are related via faculty, but in the optimal assignments of persons to courses so
that courses are staffed and faculty are not complaining.

10. Data>ntu _100_2mode
NetDraw>File>Open>UCINET>Two Mode

11. From two mode to one mode
Data>Affiliations
Dots stand for thesis committees
a, b, c stand for faculty members
Find screenshots from the online book

12. Two mode-one mode with Gephi
Data source
Node list 2
Edge list 2

13. Two mode transformation with Gephi

14. Two mode transformation with Gephi

15. Members vs. institutes

18. Two mode transformation with Gephi
Save into a Gephi file before transformation

19. Two mode transformation with Gephi

20. Exercise
Transform the presidential speech into one mode network

21. Two mode transformation with Gephi

22. Two mode transformation with Gephi