spanish revolution 23 4-2014 en
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The Spanish Revolution in Twitter (1): Hashtags, Escraches and Anti – Evictions social movement in Spain
Estrella Gualda ([email protected])Juan D. Borrero ([email protected])José Carpio ([email protected])
University of Huelva
1st IMASS conference, Methods and Analyses in Social Sciences, 23-24 April 2014, Olhão,
Portugal, http://imass.ca/imass/conference
Table of contextsFrameworkEncouraging MobilizationAdvantages and changes with Micro-bloggingAdditional advantages of micro-blogging websitesThe turn to micro-discoursesType of micro-discourses included in Twitter
Context and Topic of StudyCrisis and anti-evictions social movementsSome Success of the Anti-Evictions Social Movements in Spain
Objectives
Methods Data collectionAnalysis
ResultsQualitative analysis (Atlas ti): Codification and analysis of micro-discourses contained in the tweetsSome final codes in Atlas ti and the original terms in the tweets
Results (cont.)Basic description of the #SpanishRevolution: Global patternsCo-ocurrences of codes in tweetsQualitative analysis (Atlas ti): First Exploration of co-ocurrences of codes (#) Codes exported to Spss. Testing of hypothesis in Spss combination and triangulation between Qualitative and Quantitative analysis . Importance of hashtags in the #Spanish Revolution datasetNetwork of o-occurences among #s within the #SpanishRevolution discourseNetwork of significative correlations among # linked to the #SpanishRevolution discourseTweet’s Authors
Summarizing
Discussion
Conclusions & Following Steps
FrameworkEncouraging Mobilization
• Old Revolutions and Social Movements dissemination:• meetings, assemblies, demonstrations, and also through instruments as pamphlets,
posters, by word of mouth, and similar. • At the end of the twentieth century the process of encouraging external
mobilization used to be supported by a combination of different media:• TV, mailing, webpages or messages disseminated through mobiles.
• At the beginning of the XXI, the Web 2.0 based on the developing of Social Networks through the Internet introduced new ways of announce or call any type of protest, meeting, etc.
• Diffusion by very effective and fast means, on real-time• Twitter, Facebook, WhatsApp and similar social media, that were added to other
traditional ones. • Mobile devices (smart phones…) open up new ways to communicate and share
content.
FrameworkAdvantages and changes with Micro-blogging
• Micro-blogging changed some parameters of the collective mobilization:
• Strategies for spreading the movement, the potential scope of the dissemination, etc.
• Micro-blogging reflects the human desire to share and consume information and knowledge (Allen et al. 2011)
• Mobile devices can directly share content such as micro-blogs without Internet infrastructure
• Profits in scalability• The potential to provide content relevant to the end user without explicit
subscriptions
FrameworkAdditional advantages of micro-blogging websites
As argumented by Allen et al. (2011):• Micro-blog posts (short messages) require less time and effort to write than
‘traditional’ blog posts, yet still allow wide distribution among social networks when compared to email or instant messaging.
• Also brevity further allows the reader to easily filter large numbers of messages. • And even the broadcast nature of reduces the cognitive threshold for the writer
to decide to share and the burden of readers to process all updates. • The structure of the networks induced by micro-bloggers and their followers
makes them an ideal mechanism for rapid dissemination of information amongst ad hoc social communities.
FrameworkThe turn to micro-discourses• Discourses: From old Philosophy to recent semantics and discourse analysis (linguistics)
and conversation analysis (that study the codified language of a field of enquiry and the statements; relations among language and structure and agency, in different social and human sciences).
• It refers to written and spoken communications• Words or terms linked together that say something about: Meaning (Ferrater, 1994)• Semiotic: Set of signs (*) with different ways of significance and used with different aims
(Ferrater, 1994:917)• Signs: an arbitrary or conventional mark or device that stands for a word, phrase, etc; symbols; gestures, etc.
• Ogden and Richards (1923):• Symbolic discourses (referential)• Emotive/ expressive discourses: feelings, attitudes…
• Morris • Informative: Give information• Valorative: Say opinions• Provocative: Provoke actions• Sistemic
FrameworkThe turn to micro-discourses
• Foucault, discourse is what is said, and it is framed and connected to a paradigm in which world is organized
• discourse describes “an entity of sequences, of signs, in that they are enouncements”. The term discursive formation conceptually describes the regular communications (written and spoken) that produce such discourses
• There exist internal relations within a given discourse, and external relations among discourses
• Discourse are not isolated, but in relation to other discourses
FrameworkType of micro-discourses included in Twitter
• Twitter: users send and read "tweets", which are text messages limited to 140 characters
• Hashtags: users can group posts together by topic or type by the use of hashtags – words or phrases prefixed with a “#” sign.
Context and Topic of StudyCrisis and anti-evictions social movements
• Economic crisis in Spain• Topic: “desahucios/ evictions”, an important Spanish social
problematic today that has emerged with the economic crisis and propelled an intense ‘anti-evictions social movement’, with the drive of the PAH, the Platform of Mortgage Victims and other supports.
Context and Topic of StudySome Success of the Anti-Evictions Social Movements in Spain
• Interest of this movement• 1112 evictions stopped by the PAH (Platform of Mortgage Victims)• Rehousing of 1106 people by PAH’s Social Work• International Projection• Deeds of Assignment in Payment (Daciones en pago)• Deliver of the house in order to clear the outstanding debt (used to solve the
problem of unpaid mortgages in Spain with the crisis time). Alternative to the foreclosure (the bank follow the law and sell the house in a public auction to earn the debt.
• http://www.bankimia.com/dacion-en-pago• Increasing of organization (PAH): Empowerment, formation and auto organization
of people• Motions in Town Halls
Objectives
• To analize the use of the hashtag “SpanishRevolution” in a extracted dataset of tweets concerning ‘desahucios’.
• To describe the main other hashtags included in the tweets in which the hashtag “SpanishRevolution” was found.
• To discover the connections between this and other hashtags included in the same tweets, looking for patterns in the micro discourses produced by the hashtags.
• To determine the patterns and types of hashtags included in the tweets, that is, are the hashtags alluding to slogans, places, people, or to what?
#SpanishRevolution
MethodsData collection
Extraction of Big Data• In particular we did a follow-up of all the tweets published in Twitter
from 10 April 2013 to 28 May 2013. During these dates it was extracted all tweets that contained the chains or keywords “desahucios”, “#stopdesahucios”, and the user “@stopdesahucios”. The data extraction produced a dataset of 499,420 tweets.
• We selected the sub-sample of tweets containing the “#SpanishRevolution” for the analysis, in order to answer our objectives
• Pluralistic methodology concerning strategies and techniques of research
• With the help of the Qualitative Software Atlas ti, we codified and analyzed the micro-discourses contained in the tweets, explored co-ocurrences of codes and, finally exported the work to Spss for testing some hypothesis under a quantitative analysis, producing a combination and triangulation between Qualitative and Quantitative analysis .
MethodsAnalysis
First exploration of data (Word cruncher)Identification of significative # within the tweetsCoding of most used # in their ‘context units’ (Automatic coding)
(see example next slide)Manually coding solving problems of mis-spealling or similarsAutomatic coding in Atlas ti under one unique code, representing a significative category for further analysisExamples:12M|12m|12deMayo|12m18h|12m2013/12M2013|12Mai|12-May|may-12
ResultsQualitative analysis (Atlas ti): Codification and analysis of micro-discourses contained in the tweets
Some final codes in Atlas ti and the original termsin the tweets• 15M = #15M|#15m*|#15M2013|#15m2013
• ESCRACHE = #Escrach*|#ESCRACH*|#escrach*|#SCRACHES*|#scratch*|#Escrche|#escraces|#Escratches| #escratx*| #escrche|#*escrache*|#*Escrache*|#*ESCRACHE*|#*scrach*|#*Scrach*|#*SCRACH*|#ESCRACHE
• DESAHUCIOS= #desahucios|#Desahucios|#desahucio|#desaucios
• STOP DESAHUCIOS= #StopDesahuci*|#stopdesahuci*|#stodesa*|#StopDesahicios|#Stopdeshacuios|#StopDeshaucios|#StopDeshucios
• SPANISH REVOLUTION=#SpanishRevolution|#spanishrevolut*|#spainrevolution|#span?shrevol*|#SpanishRevolution|#SpahishRevolution|#spanishrevolutiòn
• SIN_ILP_SENADO ACABADO= #SinILPsenadoAcabado|#SinILPSenadoAcabado|#SinILPsenadoAcabado*
• NO_LES_VOTES= #NoLesVotes|#Nolevotes
• SISEPUEDE= #SíSePu*|#SiSePuede|#sisep*|#SiSePot|#SiSePuede12M|#SISEPUEDO|#SíPodem|#sípodemos
• 12M= #12M|#12m|#12deMayo|#12m*|#12M*|#12Mai|#12-May|#may-12
• 25A= #25A|#25a|# 25-abr
• ESPAÑA= #Espagne|#EsPAHña|#Espana|#espanha|#espania|#Espanol|#espanya|#España|#España
• RajoyDimisión= #RajoyVeteYa|#Rajoydimision|#RajoyDimisión|#RajoyDimisiónYa|#RajoyDimissió
• PRIMAVERA VERDE=#Primaeraverde|#PrimaveraCaliente|#PrimaveraVede|#PrimaveraVerde|#PrimaverVerde|#primaeraverde|#primavera|primaveraverde|#PrimaveraVerde|#PRIMAVERAVERDE
• 12M15M= #12M15M|#12m15m|#
• MAREABLANCA= #mareablanca|#MareaBlanca21AbrilUNETE|#MareaBlancaRELOADED|#mareblanca|#Mareasblancas
Original database: 499,420 tweets1,354 tweets including #SpanishRevolution, 22% of them are re-tweets (RT). Only 0.2% were modified tweets (MT).93.8% cite a URL within the tweet
ResultsBasic description of the #SpanishRevolution: Global patterns
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Re-tweets/ Total Modified tweets/Total
Cite 0 URL withinthe tweet/ Total
Cite 1 URL withinthe tweet/ Total
Cite 2 or moreURLs within the
tweet/ Total
Basic description of #SpanishRevolution
0 5000 10000 15000 20000 25000 30000 35000 40000
Users: Mean of followers
Users: Mean of friends
Users: Mean of statuses
2584,83
1203,15
37860,54
Data of Users
Co-ocurrences of codes in tweets
Different # in the same tweet
ResultsQualitative analysis (Atlas ti): First Exploration of co-ocurrences of codes (#)
- Importance of # in the SpanishRevolution dataset- Networks of co-ocurrences in the discourse- Network of Significative correlations among hashtags- Tweet’s Authors
ResultsCodes exported to Spss. Testing of hypothesis in Spss combination and triangulation between Qualitative and Quantitative analysis .
Importance of hashtags in the #SpanishRevolution dataset
0 10 20 30 40 50 60 70 80 90
15MNOLESVOTES
VAEOSANIDAD
MAREA_VERDE12M
12M15M25APAH
SÍSEPUEDEDESAHUCIOS
ESCRACHESTOP DESAHUCIOS
SIN_ILP_SENADOACABADOESPAÑA
INDIGNADOS_INDIGNACIÓNMAREA_BLANCA
RAJOY_DIMISIÓNILP
PRIMAVERA_VERDEREVOLUCIÓN
VIVIENDA_SOCIAL
Tags (#) by Frequency of co-ocurrence with#SpanishRevolution
MAIN DISCOURSE PRODUCED BY HASHTAGS LINKED TO #SPANISHREVOLUTION
15MNOLESVOTESVAEOSANIDADMAREAVERDE12M – 12M15M25APAHSÍSEPUEDE
Network of co-occurences among #s withinthe #SpanishRevolution discourse
cores. Different colors
CIRCLE = ActorSQUARE = Slogan UP TRIANGLE = Mobilization datesBOX = TopicsDOWN TRIANGLE = Places
Network of significative correlations among # linked to the #SpanishRevolution discourse
Size of Node: Degree
Tweet’s Authors 244 different authors in 1,354 different tweets (One and a half month of follow up)
Basic Pattern of Authorship:
1. Big centralization2. Long tail
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Centralization
Long tail
Authors (more than 10 tweets of total 1354) Frequency Percentage
Gustavo Dalmasso 700 51.7Révolutions Info 151 11.1PPSOE 35 2.6Sergio Acevedo 23 1.7DamaDuende 11 0.8
Who are they?
ResultsSummarizing
• Results suggest that the hashtag ‘SpanishRevolution’ is thematically strongly connected to other as, for instance, ‘15M’, ‘MareaVerde’, ‘NoLesVotes’, ‘Sanidad’, ‘Vaeo’ or StopDesahucios’, all of them representing alternate discourses to that of the governing party in Spain, or specific sociopolitical battles at the time of the big data extraction.
• At this time these hashtags suppose mentioning different type of phenomena, as important collective actors (‘15M’), calls for actions or slogans as ‘NoLesVotes’ or the metaphoric ‘MareaVerde’ symbolically representing the anti-evictions movements with the ‘SiSePuede’ in green color in the streets.
• Also, other hashtags as ‘#Escrache’ was especially connected to #12m, #12m15m, #15m, #NoLesVotes, #SíSePuede and #Vaeo also representing important sociopolitical dimensions at the micro discourse level.
• Main discourse of hashtags addresed around the #SpanishRevolution is focusedon ‘15M’, ‘VAEO’, ‘Nolesvotes’, a clear political turn proposed surprisenly by oneto three actors.
Discussion
• In fact, through this analysis we that around a particular hashtag exist a discursive construction if we observe connections between hashtags that have been included in the same tweets.
• Provocative discourses claming for particular actions as ‘No les votes’, • Call for action, critics, search for global social and political changes
also symbolic included under the ‘15M’ most cited hashtags in this dataset.
Conclusions & Further Research
• Emergence of non-visible connections between # and strategies behind (implications for opinion trends creation, advertisement, policies, etc.)
• Discoursive trends in Twitter through conglomerates of #. Few words to generate, defend, or sell complex ideas (anti-evictions philisophy, mobilization, etc.)
• Few actors dominate the production of “micro-discourses”, hidden leaderships in Twitter for normal users
• Technical applications to improve
Thanks a lot for your attention!
Muito obrigada pela sua atenção!• Estrella Gualda ([email protected])• Juan D. Borrero ([email protected])• José Carpio ([email protected])
University of Huelva