Apresentação no workshop Cities, Technologies and Planning, ICCSA 2104 em Guimarães, Portugal. Universidade do Minho, julho/2014

1. ICCSA - Cities, Technology and Planning, University of Minho, Guimarães, jun 30 / jul 03 de 2014
City as commons
study of shared visions by communities on Facebook
Maria Célia Furtado Rocha*, Pablo Vieira Florentino**, Gilberto Corso Pereira*
*Federal University of Bahia, ** Federal Institute of Bahia, Salvador, Brazil, Salvador, Brazil
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How groups share visions about urban public spaces… semantic networks
analysis from interactions on digital social networks (DSN)
Point of view: “expanded participation” - scope heterogeneous and
multidirectional
The main ideas expressed in the content of posts and discussions in
Facebook group pages from two groups in Italy and in Brazil
Analisys: Semantic Networks (networks of words). Identify most important
word pairs, words with higher centrality metrics
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2. ICCSA - Cities, Technology and Planning, University of Minho, Guimarães, jun 30 / jul 03 de 2014
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Common goods collectively created
Public goods:
Fundamental to human existence;
Can not be subjected to pure economic logic (water, clean air,
healthy environment, knowledge, food, health);
Internet - key resource - new possibilities of participation and
dialogues
Rodotà: the novelty is the fact that the common good, in this case, is
not just something that can serve the individual, but a good produced
by each and therefore should remain common.
Common goods – refer to social connections between people
considering goods as something used and defended for all together,
distinct of something managed or used solely in our sole interest .

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Livable spaces as a common good
How the concern of common good is being primarily expressed
through DSN that organize and are organized by social movements
that aim to improve urban public degraded area or waste (residual)
urban spaces.
The ease of interaction allowed by web 2.0 opens up many
opportunities for participation through self-expression.
We assume "expanded participation" as a way to include new social
and urban arrangements, present in cultures that use networked
communication as a means to share visions, values and produce
meanings and actions collectively.

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Salvador, Bahia, Brazil: 2.600.000 hab (2010) Potenza, Basilicata, Italy: 69.000 hab (2010)
Contexts of Case Study

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The group rises from discussions developed in DSN about urban
problems in the city of Salvador (Northeast, Brazil).
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Actions of "planting, maintenance, painting and cultural occupation of
spaces" have succeeded in some degraded and residual parts of the city
aiming to promote "an increasing number of residents with the possibility
to transform the city".
Collective Yards

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!Collective Yards
Salvador, Bahia, Brazil

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The group rises from a prior Facebook group devoted to discuss an idea
to recover an degraded area near the Basento river (Potenza City)
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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
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People share visions on the present and the future of the city through
fanpage and group foruns, since the end of 2012
Garden in Motion

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!GardeninMotion
!Potenza,Italy

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Semantic Networks
● structured representations of knowledge that are used
for reasoning and inference
● a graph consisting of vertices, which represent
concepts, and links, which represent semantic
relations between concepts
● valued networks: any link connecting concepts A and
B. Link can be qualified (directionality, strenght, sign,
meaning)
● it is an indication of number of language users (who
share the context) who agree that a link in fact exists
between concepts A and B

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Network Text Analysis (NTA)
Some beers in Brazil are produced with corn. This fact has
transformed corn in an important item of leisure, but not for feeding

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Network Text Analysis (NTA)
language and knowledge can be modeled as networks of words
and relations
data can be enhanced, for instance, with spatial and temporal
information, attributes, and weights
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NTA analyzes the existence, frequencies, and covariance of terms
and themes (classical Content Analysis)
when words are depicted as conceptual networks, one is afforded
more information, one is able to characterize concepts and
linkages according to their position within the network (forms of
centrality)

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Discovering shared views through
DSN interactions
Main ideas: words with higher centrality metrics (pairs of elements)
Unit of analysis: sentence
Relationship: a relation among all possible pairs of words forming one
single sentence is created
Metrics - pair of words:
a) FreqPar: number of occurrences of each pair;
b) Force: the division of FreqPar by total number of sentences in text
analyzed and
c) Fidelity: the division of FreqPar by the sum of the total number of
occurrences of words A or B, together or not.
Metrics such as clustering coefficient, average path and density help us
to understand and identify the kind of structure of network itself

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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 20% engaged posts
Fanpages engagement 20% engaged posts
engagement = comments + likes addressed directly to the post
engagement = comments + likes addressed directly to the post + likes addressed to
comments + shares
Data extraction – Netvizz
Statistical analysis

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2. separating all sentences and respective words in each file of both
projects - open source set of tools (modules of UNITEX, modified or not)
3. generating a semantic network and metrics of occurrences of words
and metrics of the semantic network – open source set of tools and
Gephi
group text pre-processing
1. cleaning and adjusting texts by removing or manually converting
unrecognized characters, meaningless words, signs of avoidance as the
apostrophe and eliminating auxiliary verbs - GMO 80 posts, CCS 107
posts

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Collective Yards – networked words

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Garden in Motion – networked words

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Analysis (examples)
Fig. 3. Garden in
Fig. 4. Garden in Motion g
The Parco dell'Appia An
by a biologist at the Labo
Archeologici Napoli Pomp
landscape. It is precisely th
n Motion group interactions – the networked words
group interactions – main cluster view in the networked
ntica participates in this project and hosted a lect
oratorio Ricerche Applicate Soprintendenza Spec
ei dealing with the reconstruction of the ancient
he call for this conference (204 words) that is sho
we can identify large areas shaped by a kind of cloud of words that
suggest major groups with recursive references to the following terms:
garden in motion
most emphasized words in the
second largest cluster for the
interactions are: piante (plants),
laboratorio (laboratory), Roma,
Pompei, soprintendenza
The pairs of words occurring most frequently (4) are: baratto-semi, appia-
antica, hortus-www

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Analysis (examples)
collective yards
most emphasized words
movimento / pauta / estado / bem
/ poder / social (movement/
agenda/state/good/power/social);
cidade / evento / dia / grande
(city/event/day/large)
frequency of word pairs. the highest frequencies refer to web addresses
pages.
Among the pairs of words with the highest frequency that carry meaning;
Solidarity Economy as types of economic practices that value people; the
name of an event organized by the group and the name of the group itself.

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Conclusions
the networks of words can deceive… since it is based on sentences – the
highlighted words tend to be those at larger sentences. This possibility of
misconception was greatly demonstrated in the case of Collective Yards;
in some cases, words may not appear at a given sentence, but the concept
related to them could be transmitted trough others pairs of words ;
it is necessary observe carefully the context of ambiguous words or
composed terms with an auxiliary role in the construction of meaning, when
processed by software
it is difficulty to identify the geographic information in interaction texts.
However, we believe there is a need to expand the analysis to include features
that clarify the context, especially in studies where place has symbolic value

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Conclusions
Social Network Analysis can assist in the study of composition of such urban
groups, allowing identification of relation structures in groups interactions.
Network of interactions among group members
CCS
GMO

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Social Network Analysis (SNA)
Scientific area focused on the study of relations. Based on 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
Nowadays, the term is used to refer to the analysis of any network
with the nodes of same 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, people and the films they have watched, movies
and the actors of the movies)

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Conclusions
it is fundamental to know group’s targets for studying interactions, and it is
important to consider different kinds of metrics that represent levels of
interactions, such as number of “likes”, comments, shares and so on. This
will permit cutting out textual postings that are not concerned with the
groups interests
We may consider that complex network analysis can be used in a recursive
way to guide researchers on selecting posts to be analyzed in detail,
including images and web links
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