Nodes indentified by Gender and Status

WP8-9-M1 (Curitiba – Brazil)

Kick-off Meeting (Buenos Aires – Argentine)

M18 (Rome – Italy)

Kick-off Meeting (Buenos Aires – Argentine)

Nodes indentified by Gender and Partner

WP8-9-M1 (Curitiba – Brazil)

M18 (Rome – Italy)

Nodes indentified by Continent and Country

WP8-9-M1 (Curitiba – Brazil)

Kick-off Meeting (Buenos Aires – Argentine)

M18 (Rome – Italy)

REFERENCES

First author

GENDER

Female

Male

PARTNER

CONICET

CNRS

EXTERNAL

INPE

INTA

IRD

UEA

UBA

UFPR

UFSC

UNIGE

UR

SMHI

STATUS

Ars

Doc

Ing

Phd

Pre

Ses

Tec

Ygs

▫ Not identified

CONTINENT

SA (South America)

EU (Europe Union)

Other

. Not identified

COUNTRY

Argentine

Brazil

England

France

Italy

Japan

Sweden

Switzeland

USA

Uruguay

▫ Not identified

A relational approach to CLARIS LPBA relational approach to CLARIS LPBLaura Rey 1 – Valeria Hernández 2

1 FFyL- UBA / 2 IRD

Objectives and methodologyThis poster aims to present the progress on working with Social Network Analysis (SNA), one of the methodologies chosen to carry out the ethnography of CLARIS LPB network.

In this case we decided to work with co-authorship networks of posters, using as data the list of posters available at the website of CLARIS LPB for the following project meetings: Kick Off Meeting at Buenos Aires, Argentina; WP8- 9 – M1 at Curitiba, Brazil and M18 at Rome, Italy.

For each network we considered the authors of the posters as the nodes and the relationship between them, defined in terms of joint participation in a poster, as ties.

All measures and visualizations was have made using software UCINET 6 and Netdraw.

Structural Measures

Visualizations and Atributte Analysis

Categories and attributive data were taken from the database of CLARIS LPB website. This time it was decided to work primarily with the categories of Gender, Partner, Status, Country and related with this, also with a Continent category.

Why Posters?

Because we consider that in posters shows current scientific production of principal author in association with a director and / or other colleagues with supporting roles in authorship.

Because it would establish a frame of reference / border regarding new or original knowledge since would reflecting doctoral students and young researchers work.

Kick Off Meeting: The network has a total population of 77 nodes, and the number of posters in common between them (reflected by the strengh of the ties) varies from 1 to 3, over a total of 39 posters. It is a network composed by 16 unrelated components, of which 14 contain 3 or more members, 10 contain 5 or more and 2 contain 7 or more members. The major component consists of 9 members in total. The heterogeneity in the size of the components is 92.8% and the value of fragmentation (ie. the proportion of nodes that can not reach each other) of 94.1%. The network density is 4.24% (Standard deviation = 0.2015), is to say that are present 4.24% of all possible ties. In turn, the 16 components that make up the network have the following density values ordered from 1 to 16: 63,9% (Sd = 0.4803), 100%, 100%, 100%, 50% (Sd = 0.5000), 46,7% (Sd= 0.4989), 47,6% (Sd = 0.4994), 46,7% (Sd = 0.4989), 100%, 73,3% (Sd = 0.4422), 100%, 100%, 66,7 (Sd = 0.4714), 100%, 100%, 100%.From analysis of these measures we can say that this is a low dense network with a high degree of fragmentation. It also highlights the heterogeneity in size of subgraphs, which in combination with this feature have a high degree of internal cohesion that contrasts with the density of the total network. We can observe that only three of them has a value just below of 50% and in 9 of the 16 are present the 100% of possible ties (even if we discount the 2 dyadic relationships that necessarily have a density of 100% the proportion remains high: 7 / 14).7 Cutpoints: 9, 56, 94, 98, 117, 132, 150.

WP8-9 – M1: The network has a total population of 24 nodes, and the number of posters in common between them (reflected by the strengh of the ties) varies from 1 to 3, over a total of 7 posters. It is a network composed by 3 unrelated components, one of 7 members, other of 13 members and te last one of 4 members. The heterogeneity in the size of the components is 59,4% and the value of fragmentation (ie. the proportion of nodes that can not reach each other) of 62%. The network density is 38,04% (Standard deviation = 0.4855), is to say that are present 38,04% of all possible ties. In turn, the 3 components that make up the network have density values of 100%.From analysis of these measures we can say that this is a middling dense network with a moderate degree of heterogeneity and fragmentation. It is noteworthy that the density of each of the 3 subgraphs in the network is equal to 100%, indicating that in each of them are present all possible links, and if in turn observe the visualization of this network, we see that not only are present all possible relationships within the subgraphs but also that some members have collaborated on more than one instance. In this sense, we can identify 1 clique (ie. subgraph in which each node is connected to every other node in the graph) into the largest component of the network composed by nodes: 10 - 81 - 45 to 48 - 35 - 70 to 88.None Cutpoints.

M 18: The network has a total population of 40 nodes, and the number of posters in common between them (reflected by the strengh of the ties) varies among 1 and 2, over a total of 14 posters. It is a network composed by 10 unrelated components, of which 9 contain 3 or more members, 3 contain 5 or more and 1 contain 7 or more members. The major component consists of 8 members in total. The heterogeneity in the size of the components is 88.1% and the value of fragmentation (ie. the proportion of nodes that can not reach each other) of 90.4%. The network density is 8.21% (Standard deviation = 0.2744), is to say that are present In turn, 8 of the 10 components that make up the network have a density value of 100%, while component Number 6 composed by 5 nodes and component Number 7 composed by 6 nodes have a density value of 50% (Sd = 0.5000) and 60% (Sd = 0.4899) respectively.From analysis of these measures we can say that this is a low dense network with a high degree of fragmentation and heterogenity among subgraphs. It also present here a high degree of internal cohesion where, if we discount de dyadic component, 7 of the 9 remaining have a density value of 100%2 Cutpoints: 62 and 88.

South American destination

European destination

Flowchart of CLARIS LPB Exchange Grants *

* The data use to build this diagrame was taken of the CLARIS LPB M18 Report.

REFERENCES

GENDER

Female

Male

STATUS

Ars

Doc

Ing

Phd

Pre

Ses

Tec

Ygs

▫Not identified

Visualization: Nodes Indentify by Centrality Degree and Cutpoints

Structural Measures

The network has a total population of 113 nodes, and the number of posters in common between them (reflected by the strengh of the ties) varies from 1 to 3, over a total of 60 posters. It is a network composed by 18 unrelated components, of which 17 contain 3 or more members, 12 contain 5 or more and 6 contain 7 or more members. The major component consists of 14 members in total. The heterogeneity in the size of the components is 93.1% and the value of fragmentation (ie. the proportion of nodes that can not reach each other) of 93.9%. The network density is 4.24% (Standard deviation = 0.2014), is to say that are present 4.24% of all possible ties. The measure of Centrality Degree that is depicted in the visualization represents the number of ties of each node, wich varies from 1 to 24, with a mean of 6.389 (Std Dev= 5.032).8 Cutpoints: 62, 56, 83, 94, 98, 112, 117, 132.

Union Graph

This network is the result of combining the 3 networks, is to say, Kick Off Meeting, WP8- 9 – M1, and M18 into one.