Presentation iccsa 2014

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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Common goods collectively createdPublic 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). !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)

!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 foruns, since the end of 2012

Garden in Motion


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!G

arde

n in

Mot

ion

! P

oten

za, I

taly


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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% 11,69CCS 80% 20% 13,95

likes comments likes in comments

share engagement (mean)

GMO 68% 6% 5% 21% 25,08CCS 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)

City as Commons

Fig. 3. Garden in

Fig. 4. Garden in Motion g

The Parco dell'Appia Anby a biologist at the LaboArcheologici Napoli Pomplandscape. It is precisely th

: Study of Shared Visions by Communities on Facebook

n Motion group interactions – the networked words

group interactions – main cluster view in the networked words

ntica participates in this project and hosted a lecture gioratorio Ricerche Applicate Soprintendenza Speciale Bei dealing with the reconstruction of the ancient Vesuv

he call for this conference (204 words) that is shown in

495

s

iven Beni vian the

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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ConclusionsSocial 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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Conclusionsit 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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Presentation iccsa 2014

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