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Spanish revolution 23 4-2014 en

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  • 1. 1 The Spanish Revolution in Twitter (1): Hashtags, Escraches and Anti – Evictions social movement in Spain Estrella Gualda (estrella@uhu.es) Juan D. Borrero (jdiego@uhu.es) José Carpio (jose.carpio@dti.uhu.es) University of Huelva 1st IMASS conference, Methods and An in Social Sciences, 23-24 April 2014, O Portugal, http://imass.ca/imass/confe
  • 2. Table of contexts ework uraging Mobilization ntages and changes with Micro-blogging tional advantages of micro-blogging websites urn to micro-discourses of micro-discourses included in Twitter ext and Topic of Study and anti-evictions social movements e Success of the Anti-Evictions Social Movements in Spain ctives hods collection ysis lts tative analysis (Atlas ti): Codification and analysis of micro- urses contained in the tweets e final codes in Atlas ti and the original terms in the tweets Results (cont.) Basic description of the #SpanishRevolution: Global patterns Co-ocurrences of codes in tweets Qualitative 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 dataset Network of o-occurences among #s within the #SpanishRevolution discourse Network of significative correlations among # linked to the #SpanishRevolution discourse Tweet’s Authors Summarizing Discussion Conclusions & Following Steps
  • 3. Framework Encouraging 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.
  • 4. Framework Advantages 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
  • 5. Framework Additional 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.
  • 6. Framework The 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
  • 7. Framework The 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
  • 8. Framework Type 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.
  • 9. Context and Topic of Study Crisis 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.
  • 10. Context and Topic of Study Some 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
  • 11. 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? #SpanishRevolutio
  • 12. Methods Data 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
  • 13. • 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 . Methods Analysis
  • 14. First exploration of data (Word cruncher) Identification of significative # within the tweets Coding of most used # in their ‘context units’ (Automatic coding) (see example next slide) Manually coding solving problems of mis-spealling or similars Automatic coding in Atlas ti under one unique code, representing a significative category for further analysis Examples: 12M|12m|12deMayo|12m18h|12m2013/12M2013|12Mai|12-May|may- 12 Results Qualitative analysis (Atlas ti): Codification and analysis of micro-discourses contained in the tweets
  • 15. Some final codes in Atlas ti and the original terms in 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
  • 16. Original database: 499,420 tweets 1,354 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 Results Basic description of the #SpanishRevolution: Global patterns 0,00 10,00 20,00 30,00 40,00 50,00 60,00 70,00 80,00 90,00 100,00 Re-tweets/ Total Modified tweets/ Total Cite 0 URL within the tweet/ Total Cite 1 URL within the tweet/ Total Cite 2 or more URLs within the tweet/ Total Basic description of #SpanishRevolution 0 5000 10000 15000 20000 25000 30000 35000 40000 ers: Mean of followers Users: Mean of friends sers: Mean of statuses 2584,83 1203,15 37860,54 Data of Users
  • 17. Co-ocurrences of codes in tweets Different # in the same tweet
  • 18. Results Qualitative analysis (Atlas ti): First Exploration of co-ocurrences of codes (#)
  • 19. - Importance of # in the SpanishRevolution dataset - Networks of co-ocurrences in the discourse - Network of Significative correlations among hashtags - Tweet’s Authors Results Codes exported to Spss. Testing of hypothesis in Spss combination and triangulation between Qualitative and Quantitative analysis .
  • 20. Importance of hashtags in the #Spanish Revolution dataset 0 10 20 30 40 50 60 70 80 90 15M NOLESVOTES VAEO SANIDAD MAREA_VERDE 12M 12M15M 25A PAH SÍSEPUEDE DESAHUCIOS ESCRACHE STOP DESAHUCIOS SIN_ILP_SENADOACABADO ESPAÑA INDIGNADOS_INDIGNACIÓN MAREA_BLANCA RAJOY_DIMISIÓN ILP PRIMAVERA_VERDE REVOLUCIÓN VIVIENDA_SOCIAL Tags (#) by Frequency of co-ocurrence with #SpanishRevolution MAIN DISCOURSE PRODUCED BY HASHTAGS LINKED TO #SPANISHREVOLUTION 15M NOLESVOTES VAEO SANIDAD MAREAVERDE 12M – 12M15M 25A PAH SÍSEPUEDE
  • 21. Network of co-occurences among #s within the #SpanishRevolution discourse cores. ferent colors CIRCLE = Actor SQUARE = Slogan UP TRIANGLE = Mobilization dates BOX = Topics DOWN TRIANGLE = Places
  • 22. Network of significative correlations among # linked to the #SpanishRevolution discourse Size of Node: Degree
  • 23. 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 centralization 2. Long tail 0 100 200 300 400 500 600 700 800 GustavoDalmasso RubénDrughieri 25SMurcia democraciarealmurcia BrunoJordán UnMundoSinDinero Alvarian AteneuRoig Cristianh.S. EstefaníaAlfonso JavierMtzGarrido LazarodeTormes Nulladiessineline PuppetMaster SaldaaS75 VicenteCervantes juanlumontes nedaangelofiran #occupybrussels AmyCook Bewegung30.09. DavidPellissoNavas GlobalRevolution JasminBlessed Kamchatka#1J MiguelHerencia PaulaColladosM RAKELRIVERO RocioRebazaJara ScrappyBadger VocesCríticas alfonsodiez ernstd Centralization Long tail ors (more than 10 ts of total 1354) Frequency Percentage avo Dalmasso 700 51.7 lutions Info 151 11.1 OE 35 2.6 o Acevedo 23 1.7 aDuende 11 0.8 Who are they?
  • 24. Results Summarizing • 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 focused on ‘15M’, ‘VAEO’, ‘Nolesvotes’, a clear political turn proposed surprisenly by one to three actors.
  • 25. 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.
  • 26. 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
  • 27. Thanks a lot for your attention! Muito obrigada pela sua atenção! • Estrella Gualda (estrella@uhu.es) • Juan D. Borrero (jdiego@uhu.es) • José Carpio (jose.carpio@dti.uhu.es) University of Huelva

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