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workshop e-participation
Bahia/Potenza
Potenza, Basilicata, Italy: 69.000 hab (2010)Salvador, Bahia, Brazil: 2.600.000 hab (2010)
Potenza, Università degli Studi della Basilicata, 12 jun 2014
Potenza, Università degli Studi della Basilicata, 12 jun 2014
DSN: to improve public participation in a broad sense
eParticipation
the use of digital media to mediate
and transform the relations of citizens
to governments in the direction of
more participation by citizens (Van
Dijk, 2012)
Participatory Cube
!
!
!
Leehrstandsmelder
Maerker Brandenburg
Elmshorn
Urbanias
Portoalegre.cc
Cidade democrática
0
2
4
access
pow er
communication
!
!
!
!
(Poplin, Pereira and Rocha, 2013)
● present studies seek to associate behaviors with interactions in DSN.
● applications based on social networks provide an operational context for
expanding the social sphere.
!
● it's interesting to adopt an expanded view of political participation to contemplate
new social arrangements present in cultures that use communication networks as
a medium to share views.
Potenza, Università degli Studi della Basilicata, 12 jun 2014
Social Networks:
new concept, old history
first idea: british antropologist A. Barnes (1954) paper
network = relations set between people or social groups
After that the use of a network notion as a way to designate sets
of relations between social groups expanded in social science
SNA - Social Networks Analysis: Methods, concepts, theories,
models and research used in social science, to study relations
between individuals and their regularities, to describe it - formation
and transformation - analyse effects over individual behaviour
The goal is to consider individual behaviour as a complex
subsystem of social relations that give it meaning
SNA - quantitative methodology based on graph theory - graphic
representation of social relations, measure of relations properties
Sociogramme d'une classe d'èleves de 11-12 ans. Moreno, 1934
Social Networks:
new concept, old history
Potenza, Università degli Studi della Basilicata, 12 jun 2014
Network types
Domain Aspects:
Non-Social Networks
Computer Networks; Power
Grid Networks; Road
Networks; Neural Networks ....
Social Networks 

Real Life;

Friendship 

Marriage

Sexual Contact 

Online

MobileNetworks 

Friendship in DSN
General Aspects:
Direct vs. Indirect Connection
One Mode
Two Mode
Temporal Aspects
Changing in Time − Static
Topological Aspects
(Non) Directed
(Non) Valued
Shapes (Ring, Star,...)
Potenza, Università degli Studi della Basilicata, 12 jun 2014
Candidates and donators network
Salvador municipal election, 2012
created by Gilberto Corso Pereira with:
open data (TSE, www.asclaras.org.br), open software (OutWit, OpenOffice, Gephi)
Potenza, Università degli Studi della Basilicata, 12 jun 2014
Social Network Analysis (SNA)
scientific area focused on the study of relations.
Takes graph theoretic ideas and applies them to
the social world
often defined as social networks. It is also called
network analysis, structural analysis, and the
study of human relations
today, the term is used to refer to the analysis of
any network such that all the nodes are of one
type (e.g., all people, or all roles, or all
organizations), or at most two types (e.g., people
and the groups they belong to)
Potenza, Università degli Studi della Basilicata, 12 jun 2014
social networks research areas
networks
What are their properties? What is their structure?
Does structure matter? For ex. How stable are the networks?
Are all networks similar to each other (no matter what domain)?
actors
What positions exist? What position do certain actors have? • Does
position matter? Does a role matter?
dynamics
How do actors act in networks? What typical behaviors can we find? •
How do networks form? How do they evolve?
diffusion
What flows on the on the edges in the network?
For ex. How fast does information flow? Where does it flow to?
How can we influence it?
Potenza, Università degli Studi della Basilicata, 12 jun 2014
software
Pajek – Metrics, visualization, random networks
Gephi – Metrics, visualization
OpenOffice – data input and manipulation
Ucinet – Metrics, visualization
NetVizz – Retrieval of networks from Facebook
NodeXL – Retrieval of networks from Fb and Twitter
AutoMap – semantic network
ConText – semantic network
Potenza, Università degli Studi della Basilicata, 12 jun 2014
DIGITAL SOCIAL NETWORKS AND URBAN SPACES 

Pablo V. Florentino, Maria Celia F. Rocha, Gilberto Corso Pereira
Research at laboratory LCAD, Architecture Faculty at
Federal University of Bahia – UFBa: the use of
mobile digital technologies and its influence at the
urban environment
●
just an exercise about how groups are organized to improve
residual public spaces by using digital social networks platforms
●
to expand our repertoire of research methods by exploring data
from digital social network
●
two cases, Italy and Brazil
how people are acting to modify
urban environment?
Garden in Motion (Il Giardino in Movimento, Italy)
Linha 1 Linha 2 Linha 3 Linha 4
0
2
4
6
8
10
Coluna 1
Coluna 2
Linha 1 Linha 2 Linha 3 Linha 4
0
2
4
6
8
10
12
Coluna 1
Coluna 2
Coluna 3
The group rises from a prior Facebook
group devoted to discuss an idea to
recover an degraded area near the
Basento river (Potenza City)
A design of a great park was conducted
by Studio WOP and grew up with new
supporters joining civil society and
collecting signatures on a public
petition, calling for its construction in
2012
People share visions on the present and
the future of the city through fanpage
and group forum, since the end of 2012
Collective Yards (Canteiros Coletivos, Brazil)
The group rises from discussions developed in DSN about urban problems in the
city of Salvador (Northeast, Brazil).
Actions of "planting, maintenance, painting and cultural occupation of spaces"
have succeeded in some degraded parts of the city aiming to promote "an
increasing number of residents with the possibility to transform the city".
Potenza, Università degli Studi della Basilicata, 12 jun 2014
DATA AND ANALYSES
NetVizz application
(I) textual content of posts and respective comments, just as statistics and
aggregated values of comments and likes (engagement).
(II) two kind of networks: a) the friendship network of members belonging to
each group; b) the network based on interactions between group members
through the posts (likes or comments from user X on a post from user Y)
(III) 2-mode network of fanpages of each project between two kinds of nodes:
posts and users.
2-mode networks are a particular case of social networks: two different kinds of
elements (nodes) have relations (edges) exclusively between nodes of different
types.
In the current cases, every time a user comments or likes a post in the fanpage,
a link between the post and the user is created. For all networks analyzed we
considered undirected edges between nodes.
members/followers number posts created in
GMO group Dec.13 Oct.12/Sep.13
337 days
562 80 posts Out.12
fanpage Dec.13 Jul./Sep.13
50 days
826 52 posts Jun.13
CCS group Dec.13 Jun./Jul.13
56 days
1,502 107 posts Feb.12
fanpage Dec.13 May12/Sep.13
497 days
2,704 680 posts Feb.12
Groups: We analyzed the content of 20% of the posts with the greatest
engagement (comments + likes addressed directly to the post)
Fanpages: We analyzed the content of 20% of the posts with the greatest
engagement (comments + likes addressed directly to the post + likes
addressed to comments + shares)
Potenza, Università degli Studi della Basilicata, 12 jun 2014
20% top engaged posts
likes comments engagement
(mean)
GMO 79% 21% 11,69
CCS 80% 20% 13,95
likes comments likes in
comments
share engagement
(mean)
GMO 68% 6% 5% 21% 25,08
CCS 54% 8% 6% 32% 35,59
Group pages engagement
Fanpages engagement
engagement = comments + likes addressed directly to the post
engagement = comments + likes addressed directly to the post + likes
addressed to comments + shares
Potenza, Università degli Studi della Basilicata, 12 jun 2014
27 share
14
like 28 like
64 like
90 share
16
comments
GROUPS: INTERACTION NETWORK AND FRIENDSHIP NETWORKS
The interaction and friendship networks of each group were firstly
adjusted considering the biggest component of connected nodes for
performing analyzes.
In both cases these sub-networks represented, at least, more than 90%
of original networks.
This ensure the possibility of studies and comparisons of considered
projects.
Random network (using the software Pajek and allowing comparisons
between relevant metrics such as clustering coefficient and length) and
degree distribution were also generated for each network.
Potenza, Università degli Studi della Basilicata, 12 jun 2014
Networks of interactions on posts among participants
GMOCCS
The figure shows a trend toward greater centralization in the case of CCS,
where one of the actors has a very prominent role. In the case of the Italian
group can also identify the most active actors but the leadership of the
interactions is somewhat more distributed.
Potenza, Università degli Studi della Basilicata, 12 jun 2014
For both interaction networks analyzed, comparing to the random correspondent
networks, the clustering coefficients are high and average shortest path metrics are
low. The degree distributions show no patterns in both cases. This allows us to
classify the interaction networks as Small World networks
GROUPS: FRIENDSHIP NETWORKS
CCS GMO
Potenza, Università degli Studi della Basilicata, 12 jun 2014
The degree distibution of connections and as the amount of elements in the CCS
network is higher, its graphic presents different scale in frequency axes from the GMO
network.
In these cases, few people are linked to many others, while these are connected to
very few people. So, most part of the connections belong to very few people in the
observed groups. It was possible to realize that in these structures, some people have
a higher attractiveness for new elements joining the groups, becoming fundamental for
keeping dynamics in the projects, although, inside the group, the interactions show a
clustered behavior.
GROUPS: DISTRIBUTION OF CONNECTIONS
CCS GMO
2-mode fanpage network
The high clustering coefficient and low average shortest path permit us
conclude that both projects have similar behavior and network
structures, even in different countries and cities with very distinct
population size and cultures.
CCS GMO
Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
CONCLUSIONS
The way facebook is used to communicate and spread interests and
collective actions shows similar dynamics in usage for both groups.
GMO uses fanpage to spread actions for a broader audience, while the
group forum diffuses information for group interest.
The CCS posts with more response from participants are related to
recognition from the press or students groups, while most liked posts in
fanpage are related to publicizing of movement activities (workshop,
gardening), as in GMO.
In both cases, forums reinforce relations among elements of the groups,
while fanpages work for publicizing and engaging people in groups
actions. Fanpages are used to get visibility outside, while the group
pages are used to a kind of inside conversation.
Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
Social groups from a structural
analysis approach
We can say that classic social science interpret relations among
subjects based on individual attributes and do not interpret
attitutes based on inter-individual relations
!
to the social network sociology an adequated scale to articulate
ways of sociability must be that of networks and social groups (no
more society as a whole).
!
the social networks analysis approach is regroup individuals
considering the occurrence of strong relations between them
based on observation of cohesion and density of sets they shape.
Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
CONCLUSIONS
Social data analysis reveals great similarity in the interactions and
network structures, for both groups from different countries, with
different cities not only in culture but also in size and dimensions.
The classification of networks from each case reveals a short path
between nodes in almost all networks structures.
Structure of interactions had shown great polarization in CCS
case and wider distribution around some poles in GMO case.
SNA is a exploratory tool, useful to highlight the points that must
be analyzed in a qualitative and, in some cases, manual
approach.
Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
CONCLUSIONS
SNA is a way for extracting information about agents, opinions,
interactions by use of computational tools, however, there is a need
of mixed methodologies to go further in the knowledge – not only
statistical and computational but socio spatial analysis – different
professional backgrounds are essential to a better data interpretation.
Following insights brought by social data analysis, as a future work
we believe that content analysis of discourses and meanings
contained in the posts will bring new findings.
We will explore Semantics Networking Analysis as a first
approximation to discover meaning shared by those groups about
participatory actions on urban public spaces.
research agenda: location… SNA x GIS… embedd network data,
semantic data
Potenza, Universidade degli Studi de Basilicata, 12 junho 2014

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Workshop e-participation Bahia-Potenza

  • 1. workshop e-participation Bahia/Potenza Potenza, Basilicata, Italy: 69.000 hab (2010)Salvador, Bahia, Brazil: 2.600.000 hab (2010) Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 2. Potenza, Università degli Studi della Basilicata, 12 jun 2014 DSN: to improve public participation in a broad sense eParticipation the use of digital media to mediate and transform the relations of citizens to governments in the direction of more participation by citizens (Van Dijk, 2012) Participatory Cube ! ! ! Leehrstandsmelder Maerker Brandenburg Elmshorn Urbanias Portoalegre.cc Cidade democrática 0 2 4 access pow er communication ! ! ! ! (Poplin, Pereira and Rocha, 2013) ● present studies seek to associate behaviors with interactions in DSN. ● applications based on social networks provide an operational context for expanding the social sphere. ! ● it's interesting to adopt an expanded view of political participation to contemplate new social arrangements present in cultures that use communication networks as a medium to share views.
  • 3. Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 4. Social Networks: new concept, old history first idea: british antropologist A. Barnes (1954) paper network = relations set between people or social groups After that the use of a network notion as a way to designate sets of relations between social groups expanded in social science SNA - Social Networks Analysis: Methods, concepts, theories, models and research used in social science, to study relations between individuals and their regularities, to describe it - formation and transformation - analyse effects over individual behaviour The goal is to consider individual behaviour as a complex subsystem of social relations that give it meaning SNA - quantitative methodology based on graph theory - graphic representation of social relations, measure of relations properties
  • 5. Sociogramme d'une classe d'èleves de 11-12 ans. Moreno, 1934 Social Networks: new concept, old history
  • 6. Potenza, Università degli Studi della Basilicata, 12 jun 2014 Network types Domain Aspects: Non-Social Networks Computer Networks; Power Grid Networks; Road Networks; Neural Networks .... Social Networks 
 Real Life;
 Friendship 
 Marriage
 Sexual Contact 
 Online
 MobileNetworks 
 Friendship in DSN General Aspects: Direct vs. Indirect Connection One Mode Two Mode Temporal Aspects Changing in Time − Static Topological Aspects (Non) Directed (Non) Valued Shapes (Ring, Star,...)
  • 7. Potenza, Università degli Studi della Basilicata, 12 jun 2014 Candidates and donators network Salvador municipal election, 2012 created by Gilberto Corso Pereira with: open data (TSE, www.asclaras.org.br), open software (OutWit, OpenOffice, Gephi)
  • 8. Potenza, Università degli Studi della Basilicata, 12 jun 2014 Social Network Analysis (SNA) scientific area focused on the study of relations. Takes graph theoretic ideas and applies them to the social world often defined as social networks. It is also called network analysis, structural analysis, and the study of human relations today, the term is used to refer to the analysis of any network such that all the nodes are of one type (e.g., all people, or all roles, or all organizations), or at most two types (e.g., people and the groups they belong to)
  • 9. Potenza, Università degli Studi della Basilicata, 12 jun 2014 social networks research areas networks What are their properties? What is their structure? Does structure matter? For ex. How stable are the networks? Are all networks similar to each other (no matter what domain)? actors What positions exist? What position do certain actors have? • Does position matter? Does a role matter? dynamics How do actors act in networks? What typical behaviors can we find? • How do networks form? How do they evolve? diffusion What flows on the on the edges in the network? For ex. How fast does information flow? Where does it flow to? How can we influence it?
  • 10. Potenza, Università degli Studi della Basilicata, 12 jun 2014 software Pajek – Metrics, visualization, random networks Gephi – Metrics, visualization OpenOffice – data input and manipulation Ucinet – Metrics, visualization NetVizz – Retrieval of networks from Facebook NodeXL – Retrieval of networks from Fb and Twitter AutoMap – semantic network ConText – semantic network
  • 11. Potenza, Università degli Studi della Basilicata, 12 jun 2014 DIGITAL SOCIAL NETWORKS AND URBAN SPACES 
 Pablo V. Florentino, Maria Celia F. Rocha, Gilberto Corso Pereira Research at laboratory LCAD, Architecture Faculty at Federal University of Bahia – UFBa: the use of mobile digital technologies and its influence at the urban environment ● just an exercise about how groups are organized to improve residual public spaces by using digital social networks platforms ● to expand our repertoire of research methods by exploring data from digital social network ● two cases, Italy and Brazil how people are acting to modify urban environment?
  • 12. Garden in Motion (Il Giardino in Movimento, Italy) Linha 1 Linha 2 Linha 3 Linha 4 0 2 4 6 8 10 Coluna 1 Coluna 2 Linha 1 Linha 2 Linha 3 Linha 4 0 2 4 6 8 10 12 Coluna 1 Coluna 2 Coluna 3 The group rises from a prior Facebook group devoted to discuss an idea to recover an degraded area near the Basento river (Potenza City) A design of a great park was conducted by Studio WOP and grew up with new supporters joining civil society and collecting signatures on a public petition, calling for its construction in 2012 People share visions on the present and the future of the city through fanpage and group forum, since the end of 2012
  • 13. Collective Yards (Canteiros Coletivos, Brazil) The group rises from discussions developed in DSN about urban problems in the city of Salvador (Northeast, Brazil). Actions of "planting, maintenance, painting and cultural occupation of spaces" have succeeded in some degraded parts of the city aiming to promote "an increasing number of residents with the possibility to transform the city".
  • 14. Potenza, Università degli Studi della Basilicata, 12 jun 2014 DATA AND ANALYSES NetVizz application (I) textual content of posts and respective comments, just as statistics and aggregated values of comments and likes (engagement). (II) two kind of networks: a) the friendship network of members belonging to each group; b) the network based on interactions between group members through the posts (likes or comments from user X on a post from user Y) (III) 2-mode network of fanpages of each project between two kinds of nodes: posts and users. 2-mode networks are a particular case of social networks: two different kinds of elements (nodes) have relations (edges) exclusively between nodes of different types. In the current cases, every time a user comments or likes a post in the fanpage, a link between the post and the user is created. For all networks analyzed we considered undirected edges between nodes.
  • 15. members/followers number posts created in GMO group Dec.13 Oct.12/Sep.13 337 days 562 80 posts Out.12 fanpage Dec.13 Jul./Sep.13 50 days 826 52 posts Jun.13 CCS group Dec.13 Jun./Jul.13 56 days 1,502 107 posts Feb.12 fanpage Dec.13 May12/Sep.13 497 days 2,704 680 posts Feb.12 Groups: We analyzed the content of 20% of the posts with the greatest engagement (comments + likes addressed directly to the post) Fanpages: We analyzed the content of 20% of the posts with the greatest engagement (comments + likes addressed directly to the post + likes addressed to comments + shares) Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 16. 20% top engaged posts likes comments engagement (mean) GMO 79% 21% 11,69 CCS 80% 20% 13,95 likes comments likes in comments share engagement (mean) GMO 68% 6% 5% 21% 25,08 CCS 54% 8% 6% 32% 35,59 Group pages engagement Fanpages engagement engagement = comments + likes addressed directly to the post engagement = comments + likes addressed directly to the post + likes addressed to comments + shares Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 19. GROUPS: INTERACTION NETWORK AND FRIENDSHIP NETWORKS The interaction and friendship networks of each group were firstly adjusted considering the biggest component of connected nodes for performing analyzes. In both cases these sub-networks represented, at least, more than 90% of original networks. This ensure the possibility of studies and comparisons of considered projects. Random network (using the software Pajek and allowing comparisons between relevant metrics such as clustering coefficient and length) and degree distribution were also generated for each network. Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 20. Networks of interactions on posts among participants GMOCCS The figure shows a trend toward greater centralization in the case of CCS, where one of the actors has a very prominent role. In the case of the Italian group can also identify the most active actors but the leadership of the interactions is somewhat more distributed. Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 21. For both interaction networks analyzed, comparing to the random correspondent networks, the clustering coefficients are high and average shortest path metrics are low. The degree distributions show no patterns in both cases. This allows us to classify the interaction networks as Small World networks GROUPS: FRIENDSHIP NETWORKS CCS GMO Potenza, Università degli Studi della Basilicata, 12 jun 2014
  • 22. The degree distibution of connections and as the amount of elements in the CCS network is higher, its graphic presents different scale in frequency axes from the GMO network. In these cases, few people are linked to many others, while these are connected to very few people. So, most part of the connections belong to very few people in the observed groups. It was possible to realize that in these structures, some people have a higher attractiveness for new elements joining the groups, becoming fundamental for keeping dynamics in the projects, although, inside the group, the interactions show a clustered behavior. GROUPS: DISTRIBUTION OF CONNECTIONS CCS GMO
  • 23. 2-mode fanpage network The high clustering coefficient and low average shortest path permit us conclude that both projects have similar behavior and network structures, even in different countries and cities with very distinct population size and cultures. CCS GMO Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
  • 24. CONCLUSIONS The way facebook is used to communicate and spread interests and collective actions shows similar dynamics in usage for both groups. GMO uses fanpage to spread actions for a broader audience, while the group forum diffuses information for group interest. The CCS posts with more response from participants are related to recognition from the press or students groups, while most liked posts in fanpage are related to publicizing of movement activities (workshop, gardening), as in GMO. In both cases, forums reinforce relations among elements of the groups, while fanpages work for publicizing and engaging people in groups actions. Fanpages are used to get visibility outside, while the group pages are used to a kind of inside conversation. Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
  • 25. Social groups from a structural analysis approach We can say that classic social science interpret relations among subjects based on individual attributes and do not interpret attitutes based on inter-individual relations ! to the social network sociology an adequated scale to articulate ways of sociability must be that of networks and social groups (no more society as a whole). ! the social networks analysis approach is regroup individuals considering the occurrence of strong relations between them based on observation of cohesion and density of sets they shape. Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
  • 26. CONCLUSIONS Social data analysis reveals great similarity in the interactions and network structures, for both groups from different countries, with different cities not only in culture but also in size and dimensions. The classification of networks from each case reveals a short path between nodes in almost all networks structures. Structure of interactions had shown great polarization in CCS case and wider distribution around some poles in GMO case. SNA is a exploratory tool, useful to highlight the points that must be analyzed in a qualitative and, in some cases, manual approach. Potenza, Universidade degli Studi de Basilicata, 12 junho 2014
  • 27. CONCLUSIONS SNA is a way for extracting information about agents, opinions, interactions by use of computational tools, however, there is a need of mixed methodologies to go further in the knowledge – not only statistical and computational but socio spatial analysis – different professional backgrounds are essential to a better data interpretation. Following insights brought by social data analysis, as a future work we believe that content analysis of discourses and meanings contained in the posts will bring new findings. We will explore Semantics Networking Analysis as a first approximation to discover meaning shared by those groups about participatory actions on urban public spaces. research agenda: location… SNA x GIS… embedd network data, semantic data Potenza, Universidade degli Studi de Basilicata, 12 junho 2014