social media mobilization in venezuela: a case...

Social Media Mobilization in Venezuela: A Case Study

Elías Said-Hung and Francisco Segado-Boj

ABSTRACT

This paper analyzes the practice of mobilization in the context of socialconflict via social media, using the protests in Venezuela at the beginningof 2014 as a case study. The analysis focused on the case of Twitter usingtwo of the following hashtags that trended during February and March asa reference: #PrayForVenezuela and #SOSVenezuela. The study comprisedpart of a mixed perspective of research from a random sample of 2,771tweets, 1,957 users and 1,984 published news articles via traditionalmedia (95 percent confidence +/- 2 error). The results show how socialmedia, such as Twitter, as a result of the growing control of traditionalmedia by the Venezuelan government and the lack of visible leaders in thecurrent existent scene in this country, has emerged as an unconventional,flexible, and decentralized channel for citizen’s political participation.

Keywords: Social movements, Citizen participation, Social media,Smart mobilization, Mobile participation.

During the process of the hegemonic constitution of the“Chavismo” or the “Bolivarian Revolution” in Venezuela, the Stateproceeded to assume the role of controller agent and/or socialregulator to a communicator-State (Bisbal 2009, Gómez 2014) thatwas interested in the transformation of the traditionally existentcommunicative scene (predominated by private media) to a newcontext in which the public politics of communication focused onthe search for mechanisms from the Government that guaranteedthe representation and symbolic appropriation of the politicalchavista’s project over others (opponents) in Venezuelan society.

Under the ‘Chavista´s project’, the purpose of the media wasto defend the State per se given the character of the public good(Weffer 2007). At the level of public politics, communicationbecomes relevant, such as the establishment of the Law on SocialResponsibility on Radio and Television (LSRT), which wassanctioned in 2004 and expanded in 2010 (including the broadcast

Social and Economic Studies 67:4 (2018): 235—259 ISSN: 0037-7651

236 SOCIAL AND ECONOMIC STUDIES

of informative/news content on the internet and social media withinthe Law).

Social media erupted in Venezuela as an important method ofescape from different state controls established by traditional mediain Venezuela by citizens who were interested in gaining access toinformation and the establishment of communication and relation-ships around the social transformations in Venezuela, despite anemerging increase in existing social unrest. In this social contextduring the first trimester of 2014 and second trimester of 2017, aseries of protests were led by students who showed their discontentprior to the deterioration of the quality of life and the violation ofcivil rights in Venezuela. Events that resulted in about 50 mediaplatforms closing, 200 people killed, and 4,873 people injured, and8,171 people arbitrarily arrested (Ministry of Popular Power forCommunication and Information of Venezuela 2014, Foro PenalVenezolano 2017, Huffington Post 2017).

During the protests in 2014 and 2017, the users of socialmedia, in particular Twitter, intensively used this type of resourceto spread information about these events. These events motivatedthe development of this paper, which aimed to establish elements ofanalysis that can continue the debate about the use of social media,in our case Twitter, as tools of social citizen mobilization, to obtainanswers to the following questions: 1) What is the profile of usersthat actively participated in the information coverage of theseevents? 2) What principal features characterized the socialmobilization exercised by these users? 3) What was the structure ofthe Tweets that generated the greater level of social mobilizationduring the protests studied? and 4) Was there a relationshipbetween the information flows on Twitter and the news agendapublished using the media that addressed these facts? All thesequestions will be addressed in this article in the case of the protestsin 2014, whose data is shown and analyzed here. The intention isalso to advance the study of the 2017 protests in Venezuela andother events that may serve as a basis for analysis of the proposedtopic, around this country.

The promotion of smart mobs through Twitter

We need to reflect from an interdisciplinary point of view tounderstand the transformations that are generated around the

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forms of participation that are promoted from mass communica-tion, which have cohabited with increasingly elevated communica-tion flows that are propelled by social media (Aguilera 2014).Digital and social media have changed personal relationships andthe way individuals deal with the world (Liu, Ho and Lee 2017) andthe way political communication is understood. The whole politicalsphere is enduring a process of democratization due to Internettechnologies (Schueneman, Steiger and Stier 2016) which are notonly being employed as a vehicle for top-down politicalcommunication (Segado-Boj, Díaz-Campo and Lloves-Sobrado2015) but also for enhancing political protest (Rousselin 2016). Inthis current scene, the following social movements have beenpropelled in previous years and have become well known at aninternational level: the Arab Spring, Occupy Wall Street (UnitedStates), 15M (Spain), #YoSoy132 (Mexico), and Occupy Central(Hong Kong). In the majority of cases, these movements and civilmovements that have employed social media as potentiallyeffective tools for taking on an increasingly central role, when usedas a counterweight and for social visibility against sociallyestablished de facto powers, were led by young people (Tremayne2014).

The analysis of the cases mentioned above highlights the factthat social media has turned into a temporal informal frameworkwhich drives coordinational tasks among multiple individuals, atask which until now was limited to collective organizations(Mercea 2016). This tendence is related to the concept of smartmobs, which is a term employed by Rheingold (2004) to account forthe formation and organization by people who can serve in favor ofthe solidification of an objective. Without some previous exchangeof knowledge between the parties, as a result of advances ininformation and communication technologies (ICT), the rolesassumed by contemporary social relationships are being configured(Stephens and Poorthuis 2014). Social media platforms are theelements around which cyberactivism 2.0 has been built (Sandoval-Almaza and Gil-Garcia 2014) and in many senses are considered theactual pillars of social movements. Social media use is intertwinedwith general political awareness and movement support andparticipation (Lee, Chen and Chan 2017) and positively linked topolitical engagement and action (Boulianne 2015).

Social Media Mobilization in Venezuela


Among all the social media platforms, Twitter has played aparamount role in social participation and mobilization. Its capacityto send, receive and share short content (frequently limited to 140characters) has facilitated the process of communication, informa-tion and mobilization of masses of citizens in moments of socialconfrontation or crisis (Howard, Duffy, Freelon, Hussain, Mari andMaziad 2011). Its synergy with mobile communication has createdopportunities for smart mobs, such as reappropriations of spaceand contestation of hegemonic power (Frizzera 2015). So, Twitter isseen as a new form of ‘subactivism’ which brings the opportunity tosocial groups to participate in discussions about political and socio-political issues (Bosch 2017).

Authors such as Theocharis, Lowe, Van Deth and García-Albacete (2015), and Spiro and Monroy-Hernández (2016) forexample, have debated about the meaningful role that this type ofsocial network has in demonstrations or protests, such as events inthe United States, Mexico, Brazil or Spain, since 2010. This debatehas occurred around the process of social articulation generatedfrom the massive use of hashtags, which is utilized as a system ofclassification that is generated by users for creating a betterfollowing to a determined event or fact, and to facilitate theprocesses of association between users for permitting the reading ofbrief messages, access to multiple perspectives of these messagesand the promotion of debates around determined themes(Segerberg and Bennett 2011). These elements can be used as a tacticto reinforce visibility and symbolic power of information aboutsocial movements (Wang, Liu and Gao 2016).

As Gleason (2013) highlights, there exists a group of elementsdesigned on Twitter that facilitates the task of generation andintegration of new knowledge from multiple sources: for example,sharing a web link, multimedia contents (video, audio, and image)or text. As we have indicated, contents are integrated by hashtags,which facilitate access to knowledge from a constructivistperspective, that is, from the active process led by users arounddetermined topics (Spiro and Jehng 1990); informal learning,unplanned and spontaneous, is driven by social media such asTwitter (Greenhow and Robelia 2009). Hashtags are used by Twitterusers to organize into online clusters based on their common goalsor interests (Bode, Hanna & Yang 2015) among which actions of

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knowledge sharing, community building and action promotion arebuilt (Xu, Chiu, Chen and Mukherjee 2015).

The user of social media, such as in the case study in thispaper, can follow other members, join conversations or expandviews about a fact by alluding to experts, motivated by a commoninterest and the sense of a community of news generated within thesocial network (Jenkins, Purushotma, Weigel, Clinton and Robison2006). This generates the search for models of communication thatenable the reorganization of the communicative ‘Ambient’, which ischaracterized by the incorporation and advances of 2.0 tools in thetransit of information produced by the exponential growth of theparticipants in the production and distribution of news,information, and knowledge (Said, Serrano, García and Yezers’ka2012, González and Ramos 2013, Bobkowski 2015, Carlson 2016).This production occurs via social media that can be classified, asnoted by Fumero and Garcia (2008), by its social character in thenetworks that are centered on the content produced in thecommunity by the users (e.g., Flickr) and the networks used for themanagement of the social relationships (e.g., Twitter, our casestudy).

Social movements from social media

From the point of view of sociology, social movements are definedas networks of informal interactions between pluralities ofindividuals, groups and/or organizations, engaged in political orcultural conflicts, on the basis of shared collective identities (Diani1992). Using this concept, authors such as García (2011), havehighlighted a series of features that characterize this type ofmovement: the presence of informal networks of information; thecapacity to share and achieve solidarity between involvedmembers; the collective action exercised on controversial themesand the realization of actions beyond the institutional boundaries ofthe public sphere.

One of the factors to be considered in the study ofcontemporary social movements is how to approach theiremergence (Downing 2011), as well as, how they constitutethemselves as a collective actor (Kavada 2015). We should considerthat the increase in social media has been increasinglyheterogeneous, in which the increase of the hybrid politicized



masses, as noted by Lasén and Martinez (2008), does not createcollective long-lasting identities or stable organizations.

The development of ICT has generated politics on the Internetand unconventional political participation as a means of defyingthe homogenic mass media discourse (Bonilla and Rosa 2015),during moments of high social unrest or when traditional means ofcommunication do not communicate the opinions or actions ofdifferent activists of these social movements.

The current scenes of information diffusion and theestablishment of relationships from social media and technologicaladvances require the establishment of a new agenda that helps toexamine the roles that new teams, ICT resources and current digitalscenes, acquire by the perspective explained by Downing (2009), inwhich we find ourselves in the presence of “nanomedia of socialmovements”, that is, new communication scenes in which peoplecan spread their causes or demands.

Successful social movements, including both digital andnondigital movements, as highlighted by Tremayne (2014), imply alarge social transformation in which a group of small actionsbecome pillars of broader (collective) actions. Each of these actionswill be performed by activists within these movements to generatea connection with new actors based on the recognition of commoninterests that exist in a determined moment (Tilly and Tarrow 2007).In the specific case of social media, the process of generating themark of solidarity, which refers to the collaboration and linkage ofmembers around a cause, usually emerges in the first stages of thesocial movements generated from activism 2.0, which areperformed by individuals who share an interest or common goal(Tremayne 2014).

In the specific case of Twitter, the issue explained in theprevious paragraph emerges between different nodes of networks,which are shaped by users, who employ hashtags and mentions tothird parties, which is a mechanism that guarantees theproliferation of causes across media by different Tweets publishedby one user to another and that do not always share the samegeographic space or possess common identities, if not completelydivergent (Raban, Ronen and Guy 2011, Segerberg and Bennett2011). As highlighted by Tremayne (2014) or Arnold (2011), thisaction justifies the development of studies that would help todiscover relevant characteristics around different social movements

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that erupted in digital spaces, such as the following areas: thecomposition and profile of members that integrate the movements,the type of centrality displayed by the Internet that forms a part ofthese movements, and the messages that aid in the interaction of theparticipants, that is, the level of impact generated via publishedmessages in external media to the movement for its revitalization.

METHOD

The project is classified in a quali-quantitative perspective ofresearch that considers three stages of development that addressdistinct facets of student protests in Venezuela during the firsttrimester of 2014. In the first stage of analysis, the principalcharacteristics of participation in social media were examinedduring events of conflict in Venezuela at the beginning of 2014, withemphasis on the social network Twitter. Content posted by socialmedia can be analyzed in order to extract meaningful information(Ceron and Negri 2016). Two units of analysis were examined: 1)the User that actively participated via the social network; and 2) theMessage spread by these users. The population of study includedall users and messages that where involved with the hashtags#SOSVenezuela and #PrayForVenezuela between 13 February and12 March 2014, that is, during the first month of the student protestson a national level in Venezuela.

The hashtags for the proposed theme were the most trendingtopics in Venezuela during the time period of the study, whichcorresponds with Trendinalia (url: http://www.trendinalia.com/). Inthe case of the hashtag #PrayForVenezuela, a total of 2,877,842Tweets were registered during the period of analysis; in the case ofthe hashtag #SOSVenezuela, this tweet reached 7,732,063 messages.Initially, a random sample was estimated and grouped by hashtagsand by the daily number of Tweets, with a level of confidence of 95percent and a margin of error of +/- 5 percent. The sample wascomposed of 2,771 Tweets and a total number of 1,957 users, whichcomplied with the following selection criteria: 1) At the level ofusers of Twitter: evidence of real existence (no robots), withminimum information in their bios for the development of theanalysis proposed in this study; and 2) At the level of Tweets: norepeated messages, incoherent or with low or null levels ofsuitability or with inappropriate or unidentifiable content



(messages that utilized hashtags with commercial ends or themeswithout some relationship to the protests in Venezuela).

The total identification of the sample units in this study wasachieved based on the individual confirmation of each one of theanalyzed messages and the contents of the bios of the users thatspread them. The selection of the final sample was considered in themeasurements, as shown in Table 1.

Table 1: Variables for the analysis of Tweets and users, taken as a sample

Variables for measurement of users Variables for measurement of Tweets

TypeNumber of followers

Number followingProfession

GenderAge

LocationSocial relevance

Political affiliation

Date of publication of TweetNature of Tweet

Number of RT generated by TweetNumber of favorites generated by

TweetMentions other users

Type of Tweet (format of content)Hashtags mentioned

Type of imagePolitical affiliation of the message

Type of messageAttitude of the message

Source: Produced by the authors.

The second stage of the analysis for the development of thisstudy involved an analysis of the news agenda and the newscoverage offered by legacy media and the correlation that it couldexist with the collected tweets in the sample of this study.

The news was selected via Google’s indexed news. Despite theinherent limitations of analyzing the news coverage of the studentprotests in Venezuela during the analysis period, this system ofdigital indexation was conceived as the most viable method forobtaining a more complete and general viewpoint of the newsagenda of this conflict: 1) the limitations of available human andtechnical resources for the total registry of published news inVenezuela during the analysis period, on behalf of the team incharge of this study; and 2) the online presence of the majority ofcommunication media in Venezuela.

Due to the impossibility of accurately determining the totalnumber of generated news events during this study period, the

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design of a simple random sample for infinite populations orunknown populations was selected, with a level of confidence of 95percent and a margin of error of +/- 2 percent, which was composedof a minimum of 1,984 news events. At this value, an additional 10percent was added for the effect of replacement. Therefore, thesample at this stage was composed of 2,140 news events; newsitems that were poorly dated or were unconnected with the themeor with news dedicated to topics other than the news were omitted.The total of the selected sample units was directly delivered fromthe web portals of media.

The third and last stage of the analysis was centered on thecontents of the Tweets and previously identified news, which wereanalyzed in their totality via the application of the technique ofcontent analysis. Based on the generated textual information duringthis stage, they were able to infer the relationships that crossbetween the lexical units (Armony, 1997) of the totality of news andthe Tweets considered for the study.

RESULTS

The results generated from the information contained in theprofiles of users of Twitter were integrated in the study sampletaken for the approach of the study question (n = 1,957). The genderof the majority of the users (79 percent) was male, whereaspercentage of female users or users who did not apply under thiscategorization (institutional users) comprised 13 percent and 8 per-cent respectively of the analysis in this study. The majority of theseusers (49.4 percent), who were nationals of Venezuela, presented adirect link with the events in Venezuela, whereas the nationalitiesof the participants in the remaining cases (35.9 percent) could not bedetermined due to the lack of information in their profiles orbecause the participants are citizens of other countries in LatinAmerica (7.5 percent), North America (4 percent), Europe (2.9 per-cent) or Asia/Oceania (0.4 percent).

At the level of their presence on Twitter, analyzed users (n =1,957) had a high level of popularity on Twitter, based on theaverage length of time as members of this social network (µ = 3years). The average considers an intensive level of dailyparticipation by users in this digital space. In addition, they have anaverage (µ) of followers and followed users (7,289 users and 1,351



users, respectively), that is, they are users that, according to Barone(2010) or Said and Arcila (2013), can be considered to be “everydayusers” who do not have a high network of contacts because theypossess circles of influence of relatively small size but have a highimpact reach via Twitter.

The middle position in the ranking of the analyzed users inthis social network (µ = position 27,273,249), which correspondswith TwitterCounter, would emphasize an average profile or no-leadership profile similar to the majority of users employed assample units for our proposed study. The low level of influence onTwitter is related to the type of public relevance to the analyzedbecause 96 percent of these users did not seem to possess thesefeatures, based on the exposed information in their profiles.

Regarding the political affiliation of analyzed users aroundthe hashtags used as a reference, the data reflects how the majoritypublished a critical position (opponent) against the governmentof Venezuela (80 percent of analyzed cases) via Tweets, whereas19 percent maintained a neutral position (not distinctly identifiedwith some of the majority political tendencies in Venezuela),and approximately 1 percent showed a favourable position(Chavista).

Social mobilization of analyzed users

Regarding the type of published content in the Tweets that werecreated or published by the analyzed users, Figure 1 shows howthree classes of messages can be observed: 1) Messages that directlymention the occurring events during different student protests inwhich users directly produced Tweets of their criticisms and/orpositions about these facts; 2) Social or general messages, which aremarked as favourites by analyzed users, in which they refer tocultural and/or political personalities in addition to related contentwith calls for peace in Venezuela; and 3) Messages that advocate theresolution of existing social conflict or the development of relatedactions with these events during the study period. These types ofmessages concentrate on the answered Tweets by the analyzedusers.

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Regarding the profile of messages that generated the greatest socialmobilization, which were answered or marked as favourites by theanalyzed users within the total of the sample of selected Tweets(N=2,771), the following conclusions were formed (see Table 2).

In addition to the information explained to this point, Table 5enables us to see how the social mobilization from Twitter centeredaround the hashtags in the case study among the analyzed users,which reflected a greater percentage among these Tweets with amixed format, that is, text plus multimedia resource. Tweets thatonly contained text generated an important percentage ofmobilization around student protests in Venezuela during the study


Figure 1: Clouds of main expressions published by analyzed users according totype of published Tweet

Source: Produced by the authors.Notes: N - Tweets = 2,771; N - News = 2,140


Table 2: Results of analysis carried messages

The Tweets marked as favouritesgenerated the greatest mobilization(µ = 703), compared with the Tweetsthat were answered (µ = 208). In thefirst case, the messages with thegreater average of replies wererelated to images and/or videos(some without written text), with a µof 2,646. In the second case, themessages written in English exhibitedgreater mobilization (µ = 2,255).

Regarding the type of messages, themobilization of analyzed users viaTwitter presented features thatdistinctly differentiated betweenreplied messages versus messagesmarked as favourites (see Table 3).On the level of replied Tweets, agreater diversity of typologies in thecontents is observed, with thecommunicated Tweets (e.g., “RT@albitcaban: PARAGUAYANMINISTER HANDS OVER PROOFAGAINST MADURO @TACHIRA#SOSVENEZUELA #SOSVzlahttp://t.co/cuLwECBX”) andannouncements related to theanalyzed events generate the greatestmobilization (e.g., “RT @Mryaakov: Ifyou have friends in the popularzones, let them obtain the info.Caracas is not only Altamira norMaracaibo La Lago #SOSVenezuela”).However, Tweets with insults (e.g.,“You don’t have many left miserabledictator @NicolasMaduro#PrayForVenezuela#ElQueSeCansaPierde [HeWhoTiresLoses]http://t.co/j0mWWbc9Ef”) have lessweight among the samples; in thecase of Tweets that are marked asfavourites, the announcementsconcentrate the most weight duringmobilization among analyzed usersfor the events in the study period.Mentions to other users within the

achieved mobilization from Twittersurrounding the events utilized as acase study in Venezuela tended to begreater in the Tweets that weremarked as favourites (µ = 246) at thelevel of replied Tweets (µ = 697).

Regarding message structure, themobilization of analyzed users alsopresents distinct differences betweenthe answered messages and/or themessages marked as favourites (seeTable 4). In the case of repliedTweets, the greatest mobilization wasobserved in Tweets that uniquelyshowed links or URLs of contentrelated to the protests. In the case ofTweets marked as favourites, themessages that only contained textgenerated the greatest mobilization.

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Regarding the social mobilizationcreated by analyzed users in relationto their political affiliation, thecollected data shows us how thereplied Tweets and Tweets marked asfavourites that did not present anopposing position (e.g., “Whensomething happens by Maduro, atree falls. This is the start of your fall,Maduro, it has already happened toyou #venezuelanoestasola[venezuelaisnotalone]#PrayForVenezuela”) or that werefavorable of the Venezuelangovernment (e.g., “RT @TrapieLLo:What a coincidence that thecantantuchos that declared#PrayForVenezuela are “ExclusiveWarner Artists” of #TimeLifeCNN!. . . ”) were Tweets that generated thegreatest mobilization around thestudent protests during the period ofstudy (µ = 243 and µ = 1,053,respectively). In the case of Tweets ofopposing stances to the government,these Tweets were in second positionin terms of the generation ofmobilization, in both cases mentionedhere (µ = 189 and µ = 513,respectively). The Tweets withfavourable stances toward theVenezuelan government generatedless mobilization among analyzedusers (µ = 127 in the case of the mostreplied Tweets and µ = 334 in the caseof the Tweets marked as favourites).

Regarding the attitude within theTweets that generated socialmobilization among analyzed users,the data does not show that Tweetswith messages with positive attitudeswere Tweets that had the greatestimpact, in the case of the Tweetsmarked as favourites (µ = 1,050),whereas in the case of the repliedTweets, a distinct influence of theattitude is not observed (µ = positive= 211, µ-negative = 190 and µ-neutral=220). An example of Tweetsaccording to attitudes of the analyzedusers is as follows: “They are notgoing to defeat us, nobody stops apeople that has conviction.#PrayForVenezuela#MaduroRenunciaYA[MaduroResignNow]#MovilizadoresCoro #1M” (Tweetwith a positive attitude); “RT@mindig_: Another innocent dies,another child. What a miserabledisgrace. Geraldine Moreno, RIP.#SOSVenezuela #AmeliachAsesino[AmeliachMurderer] #HelpUs¨(Tweet with a negative attitude); and“RT @caramos61: That which themedia does not describe: SanDiegoCarabobo TODAY #SOSVenezuela@VenteCarabobo @VenteVenezuelahttp://t.co/tuzUXoLPhI¨ (Tweet with a neutral attitude).

Source: Produced by the authors.



Table 3: Mobility of analyzed users according to the typology of the publishedmessage in the Tweets

Type of Message Average of responded Tweets* Average of Tweets marked as favorites**

Announcement 271.81 2,249.05Statement 367.90 856.70Grievance 213.67 425.27Description 184.12 685.45Indicators 172.19 665.14Insult 137.97 382.82Opinion 204.81 611.89

Source: Produced by the authors.Notes: N - Tweets answered = 2771; N-Tweets marked as favourites = 2771

Table 4: Mobility of analyzed users according to message structure

Average of Tweets Average of marked as

Message structure replied Tweets* favourites**

Only link or URL 1,252.00 758.83Only image 141.00 264.00Only multimedia (video, audio or image) 111.93 234.24Only text 173.42 1,484.47Text + audio 118.22 403.22Text + link 239.87 615.66Text + image 206.62 328.66Text + video 270.10 523.32

Source: Produced by the authors.Notes: N-Tweets answered = 2771; N-Tweets marked as favourites = 2771

period. In the case of the Tweets that published content that wasonly presented in multimedia format, the mobilization percentageswere very low or non-existent among sampled users.

As shown in Table 6, the re-Tweeted Tweets presented agreater average of responses on the part of other users who activelyused hashtags that were employed as case studies. The answeredTweets presented a greater average of favourites on the part of thirdactors.

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Table 5: Percentage of social mobilization generated by analyzed users according tothe nature and format of the Tweets

Format

Mixed (text Only Multimedia Only TextNature of Tweet + multimedia (Video, audio,

resource) image)

Re-tweeted 55.8 percent 2.3 percent 41.9 percentReplied 75.0 percent 2.1 percent 22.9 percentPublished initially by users 55.6 percent 2.7 percent 41.7 percent

Source: Produced by the authors.Notes: N-Tweets answered = 2771; N-Tweets marked as favourites = 2771

Table 6: Average of social mobilization among analyzed users according to type,response and marking as favourite Tweets published by analyzed users

Average

Type of Tweet Answered Tweets Tweets marked as favourites

Re-tweeted 273.59 458.40Replies 213.369 797.21Initially published by users 189.529 525.06

Source: Produced by the authors.Notes: N - Tweets answered = 2771; N - Tweets marked as favourites = 2771

News agenda versus user engagement on Twitter

Figure 2 shows how Twitter served as a space for high socialmobilization around student protests in Venezuela, on the part ofanalyzed users. From a citizen’s point of view, Twitter covered thenews flow more extensively than Venezuela’s existing media duringthe study period.

If we compare the information presented in Figure 2 with theprincipal themes addressed on the dates with distinct differencesbetween information flows generated by the media in Venezuelaand the information flows generated by analyzed users (see Table 7)via Twitter, a distinct political positioning is evident in bothscenarios. In the case of the analyzed Tweets, which were linked



with the hashtags utilized as case studies, they maintained adistinct critical position that rejected the government but wassupportive toward student demonstrators. In the case of the mediain Venezuela, the principal themes addressed in the news werefavourable toward the government and attempted to relate theprotests with organized plots on an international level or with athesis that related these protests with attempts at institutionaldestabilization.

Considering the existing correlation between the number ofdaily published news items versus the number of Tweets made as asample for the approach of the study topic, Table 8 illustrates howa significant relationship does not exist, that is, evidence of arelationship between social mobilization exercised by analyzedusers via replied Tweets or Tweets marked as favourites by usersand the published news agenda for the traditional existing media inVenezuela has not been identified.

Figure 2: Quantity of published news versus quantity of Tweets generated byanalyzed users

Source: Produced by the authors

Notes: N - Tweets = 2,271/N = News = 2,140

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Table 7. Differences between information flows generated by media in Venezuelaand communication flows by analyzed users

Dates of Principal topics Principal topics addressed via reference addressed by analyzed media in Venezuela

users on Twitter

February 16 Messages associated with The news on this date focuses on thethe protests initiated government’s reaction to the developed in the days before students protests and the support given to the concentrated in the plaza protests from different countries. Altamira and demanded the liberation of students detained by the government in previous protests; state power is accused of torturing the detained students.

February 22 The messages focus on the The identified news significantly development of a new focuses on the relationships between march convened by the Venezuela and the United States in the Democratic Unity middle of social tension and the Roundtable (MUD); a pro- possibility of dialogue between the government march named government and the opposition.the “March of Women” is developed.

February 24 The messages on this date The collected news accounts for the refer to the suppression of predominant use of barricades in thethe protests by the armed streets or “guarimbas”1 as a means of forces of the Venezuelan protest, their location, consequencesstate and the international and use on the part of the government support to the victims of of this situation. It highlights the this repression. coverage of the incident by Nicolás

Maduro to members of the opposition to initiate a dialogue.

February 28 – A high proportion of The analyzed news refers to the state-March 1 messages include messages ments by Nicolás Maduro about the

of support regarding the consequences of protests in respect toprotests from different dead members of the armed forces, parts of the world and the economic consequences of thecontinued reporting of blockades and the messages ofgovernment excesses in support received by his government containment of the protests. from some world leaders.

1. Guarimbas are a form of protest in which the people protect themselves at a secure pointuntil improved conditions make it possible to leave and continue with the planned activity.



March 3 Messages refer to the The news concentrates on the position commentaries about of a group of countries or entities thatVenezuela made by reject how the government of Nicolásmultiple artists in the Maduro handles the crisis. Govern-presenting of the ment authorities denounce theOscar awards, where development of a campaign ofvarious award-winners discredit against Venezuela at the referred to the situation Oscar awards.of human rights in Venezuela and Ukraine.

Source: Produced by the authors.Notes: The dates utilized to create this table were obtained from Figure 2, majordifferences between the numbers of published news items in the media in Venezuelaversus the number of Tweets generated by analyzed users were observed during thestudy period.

Table 7 (cont’d). Differences between information flows generated by media inVenezuela and communication flows by analyzed users

Table 8: Correlation between the number of published news items in traditionalmedia in Venezuela and Tweets published by analyzed users during the study

period

Quantity of Quantity of Average of Average ofNews Tweets answered Tweets

Tweets marked as favourites

Pearson Correlation 1 .220 .010 -.116Quantity of NewsSig. (bilateral) .260 .959 .558N 28 28 28 28

Source: Produced by the authors.Notes: N = 28 days with base = 2,771 Tweets and 2,140 News

CONCLUSIONSIn addition to being marked in recent history by an increasingprocess of social tension, the current Venezuelan scene has servedto propel processes for the promotion of new scenes ofcommunication, which are unconnected to traditional scenes,which have been taken by citizens for the diffusion of informationof different events occurring in Venezuela. The case study helps to

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reiterate the ideas proposed by Rheingold (2004) regarding socialmedia, such as Twitter in our case, as contributors to the promotionof new forms of smart mobs, from citizen participation-oriented tothe spreading of content and information on the basis of users whoparticipated in the social diffusion of student protests in Venezueladuring 2014. It also allows us to recognize differences between thenews flow broadcast via traditional media versus information flowsthat are shared and socialized using these types of social media.

In the case of Venezuela, as a result of the increasing mediasiege promoted by the State, since early 2000 till present, citizenshave been seeing social media as an unconventional, flexibleplatform, without clear identification of political leaders and asdecentralized channels for exercising their citizen’s politicalparticipation (Castells 2009), through collecting, managing andsharing information about the protest incidents that occurred in2014. Meanwhile, mass media covered part of these events,developing themes related to, but not focused on them. Therefore,the data allows us to reaffirm the ideas explained by Howard et al.(2011) and Junco, Elavsky and Heiberger (2013) regarding theimpact by Twitter on the construction of links between analyzedusers, via the intensive diffusion of information and opinionsduring the considered events, and the significant role of a socialnetwork, such as Twitter, in countries such as Venezuela, in whichthe State exercises an increasing role in communication (Bisbal 2009,Gómez 2014).

The findings by Papacharissi and De Fátima Oliveira (2012) orGleason (2013), who attempted to establish the significant role ofTwitter in social movements in the United States, Egypt or Tunisia,also hold in the Venezuelan case. The mainstreaming of contentspread by the users using selected hashtags for the development ofthis study permitted them a greater following of events. It alsoallowed a debate of these events by accessing multiple perspectivesfrom the different types of messages presented in this article(Segerberg and Bennett 2011). Something that allows improving thevisibility and the symbolic power of information about socialmovements (Wang et al. 2016), related to the Venezuelan protests in2014.

Through the case analyzed in this paper, we can appreciate areorganization of the ‘Communication Ambient’ in Venezuelawhich has promoted the integration of Twitter and other social



media to address the debates of topics of common interest bycitizens of this country (e.g. the violence and violation of humanrights lived during the protests in 2014).

We have been able to explain the generation and integration ofnew knowledge from the different shared sources from differenttypes of messages of greater impact during the social mobilizationexercised by the users from this digital space regarding the protestsin our case study. Therefore, it reaffirms Spiro and Jehng’s (1990)argument regarding the active process led by analyzed users andthe process of informal learning, which is unplanned andspontaneous, that is promoted by social media, as suggested byGreenhow and Robelia (2009). This process is performed via themanagement of established social relationships among users(Fumero and Garcia 2008) who form part of the hybrid politicizedmass with a common cause (critical position against the Venezuelangovernment) with features that were previously outlined by Lasénand Martínez (2008). According to Tilly and Tarrow (2007),Downing (2011) and Tremayne (2014), the use of Twitter as the‘nanomedia’ of the social movements in Venezuela during the studyperiod is based on their 2.0 activism and on social transformation ofthe scale mediated by the impact of social media, as observed in thiswork.

REFERENCESAguilera, Rafael. 2014. Participación ciudadana, servicios públicos y

multiculturalidad. In Actualidad de los servicios públicos en Iberoamérica,1-38. Mexico: Universidad Nacional Autonoma de México.

Armony, Victor. 1997. El análisis de datos cualitativos en ciencias sociales:Nuevos enfoques y herramientas. Revista de Investigaciones Folklóricas12: 9-16.

Arnold, Gretchen. 2011. “The Impact of Social Ties on Coalition Strengthand Effectiveness: The Case of the Battered Women’s Movement in StLouis.” Social Movement Studies 10 (2): 131-150.

Barone, Lisa. The 5 Types of Influencers on the Web. 2010. http://smallbiztrends.com/2010/07/the-5-types-of-influencers-on-the-web.html (Accessed on May 22, 2018).

Bisbal, Marcelino. 2009. Medios Comunitarios: ¿Democratización y pluralismoen el paisaje mediático del país. Venezuela: National Association ofJournalists.

255

Bobkowski, Piotr. 2015. “Sharing the News Effects of Informational Utilityand Opinion Leadership on Online News Sharing.” Journalism &Mass Communication Quarterly 92 (2): 320-345.

Bode, Leticia, Alexander Hanna, and Junghwan Yang. 2015. Candidatenetworks, citizen clusters, and political expression: Strategic hashtaguse in the 2010 midterms. The ANNALS of the American Academy ofPolitical and Social Science 659 (1): 149-165.

Bosch, Tanja. 2017. Twitter activism and youth in South Africa: The case of#RhodesMustFall. Information, Communication & Society 20 (2): 221-232.

Bonilla, Yarimar and Jonathan Rosa. 2015. # Ferguson: Digital protest,hashtag ethnography, and the racial politics of social media in theUnited States. American Ethnologist 42 (1): 4-17.

Boulianne, Shelley. 2015. Social media use and participation: A meta-analysis of current research. Information, Communication & Society 18(5): 524-538.

Carlson, Matt. 2016. Embedded links, embedded meanings: Social mediacommentary and news sharing as mundane media criti-cism. Journalism Studies, Sheffield 17 (7): 915-924.

Castells, Manuel. 2009. Communication Power. Oxford: Oxford UniversityPress.

Ceron, Andrea, and Fedra Negri. 2016. “The Social Side of Public Policy:Monitoring Online Public Opinion and Its Mobilization During thePolicy Cycle.” Policy & Internet 8 (2): 131-147.

Diani, Mario. 1992. The concept of social movement. The SociologicalReview 40 (1): 1-25.

Downing, John. 2009. Nanomedios de Comunicación. Barcelona: UNESCOChair & Universitat Autónoma de Barcelona.

Downing, John. 2011. Encyclopedia Social Movement Media. Thousand Oaks,CA: SAGE Publications.

Frizzera, Luciano. 2015. “Mobile Media as New Forms ofSpatialization.” Interdisciplinary Science Reviews 40 (1): 29-43.

Foro Penal Venezolano. 2017. Reportes sobre la represión del Estado enVenezuela. https://foropenal.com/category/publicaciones/nacionales/reportes-de-represion/ (Accessed on February 15, 2018).

Fumero, Antonio, and Jose Garcia. 2008. Redes sociales. Contextualizaciónde un fenómeno ‘dos-punto-cero’. Revista Telos 76. http://telos.fundaciontelefonica.com/telos/articulocuaderno.asp@idarticulo=3&rev=76.htm (Accessed on May 22, 2018).



Garcia, Lidia. 2011. Apuntes sobre perspectivas de estudio de losmovimientos sociales. Un enfoque desde la comunicación en redessociales. Virtualis 4: 127-139.

Gleason, Benjamin. 2013. #Occupy Wall Street: “Exploring InformalLearning about a Social Movement on Twitter.” American BehavioralScientist 57 (7): 966-982.

Gómez, Ava. 2014. Venezuela entre el Estado Comunicador y el pluralismomediático. Zer 19 (36): 221-249.

González, Sonia, and Fatima Ramos. 2013. El uso periodístico de Facebooky Twitter: un análisis comparativo de la experiencia europea. Historiade la Comunicación Social 18 (November): 419-433.

Greenhow, Christine, and Beth Robelia. 2009. “Informal Learning andIdentity Formation in Online Social media.” Learning, Media andTechnology 34 (2): 119-140.

Howard, Philip, Aiden Duffy, Deen Freelon, Muzammil Hussain, Will Mariand Marwa Maziad. 2011. Opening Closing Regimes: What Was the Roleof Social Media during the Arab Spring? Seattle: University ofWashington.

Huffington Post. En 2017, 49 medios han cerrado en Venezuela.https://www.huffingtonpost.com.mx/2017/08/26/en-2017-49-medios-han-cerrado-en-venezuela_a_23186682/ (Accessed on February 15,2018).

Jenkins, Henry, Ravi Purushotma, Margaret Weigel, Katie Clinton, andAlice Robinson. 2006. Confronting the Challenges of ParticipatoryCulture: Media Education for the 21st Century. London: MacArthurFoundation & MIT Press.

Junco, Reynol, Michael Elavsky and Greg Heiberger. 2013. “Putting Twitterto the Test: Assessing Out comes for Student Collaboration,Engagement and Success.” British Journal of Educational Technology 44(2): 110-126.

Kavada, Anastacia. 2015. Creating the collective: social media, the OccupyMovement and its constitution as a collective actor. Information,Communication & Society 18 (8): 872-886.

Lasén, Amparo and Igor Martínez. 2008. Movimientos, movidas y móviles:un análisis de las masas mediatizadas. In Cultura digital y movimientossociales, coords. Igor Sádaba and Angel Gordo, 243-266. Madrid: LaCatarata.

Lee, Francis, Hsuan Chen, and Michael Chan. 2017. Social media use anduniversity students’ participation in a large-scale protest campaign:

257

The case of Hong Kong’s Umbrella Movement. Telematics andInformatics 34 (2): 457-469.

Liu, John, Mei Ho, and Louis Lu. 2017. Recent themes in social networkingservice research. PloS One, California, 12 (1). http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0170293 (Accessedon February 15, 2018).

Lobo-Guerrero, Catalina. 2015. El diario opositor ¨tal Cual¨ es la últimavíctima del cerco a la prensa. http://internacional.elpais.com/internacional/2015/02/26/actualidad/1424988906_080895.html(Accessed on April 2, 2015).

Mercea, Dan. 2016. The social media overture of the pan-European Stop-ACTA protest: An empirical examination of participatorycoordination in connective action. Convergence 22 (3): 287-312.

Ministry of Popular Power for Communication and Information ofVenezuela. 2014. Protestas han dejado 42 muertos, 873 lesionados y224 privados de libertad. http://www.minci.gob.ve/2014/05/protestas-han-dejado-42-muertos-873-lesionados- y-224-privados-de-libertad/ (Accessed on April 2, 2015).

Papacharissi, Zizi, and Maria Oliveira. 2012. “Affective News andNetworked Publics: The Rhythms of News Storytelling on #Egypt.”Journal of Communication 62 (2): 266-282.

Piña, Elsa. 2010. Intolerancia a la crítica y hegemonía comunicaciónmenoscaban libertad de expresión. In ¿Por qué nos odian tanto? Estadoy medios de comunicación en América Latina, coord. Omar Rincón, 149-164. Bogotá: Friedich Ebert Stiftung.

Raban, Daphne, Inbal Ronen and Ido Guy. 2011. “Acting or Reacting?Preferential Attachment in a People-Tagging System.” Journal ofAmerican Society for Information Science and Technology 62 (4): 738-744.

Rheingold, Howard. 2004. Multitudes inteligentes. La próxima revoluciónsocial. Madrid: Gedisa.

Rousselin, Mathieu. 2016. Modern communication technologies and theextension of the territory of struggle: Conceptualising Tunisia’sjasmine revolution. New Media & Society 18 (7): 1201-1218.

Said, Elias, and Carlos Arcila. 2013. “Online Opinion Leaders in LatinAmerica and the Middle East: The Case of the Top 20 Most-ViewedTwitter Users.” Informação & Sociedade: Estudos 23 (2): 139-155.

Said, Elias, Ana Serrano, Elvira García, and Lyudmyla Yezers´ka. 2012.“The Management of the Social Media at the Iberoamerican’s MassMedia.” Communication & Society 26 (1): 69-94.



Sandoval-Almazan, Rodrigo and Jose Gil-Garcia. 2014. Towardscyberactivism 2.0? Understanding the use of social media and otherinformation technologies for political activism and socialmovements. Government Information Quarterly 31 (3): 365-378.

Schuenemann, Wolf, Sebastian Steiger and Stefan Stier. 2016. Is there atransnationalization and democratization of public spheres? Acomparison of two global political issues. Zeitschrift Fur VergleichendePolitikwissenschaft 10: 233-257.

Segado-Boj, Francisco, Jesus Diaz-Campo and Beatriz Lloves-Sobrado.2015. Líderes latinoamericanos en Twitter. Viejas costumbres paranuevos medios en tiempos de crisis políticas. Revista Latina deComunicación Social 70: 156-173.

Segerberg, Alexandra and William Bennett. 2011. “Social Media and theOrganization of Collective Action: Using Twitter to Explore theEcologies of Two Climate Change Protests.” Communication Review14: 197-215.

Spiro, Rand, and Jihn-Chang Jehng. 1990. “Cognitive Flexibility andHypertext: Theory and Technology for the Nonlinear andMultidimensional Traversal of Complex Subject Matter.” InCognition, Education and Multimedia: Exploring Ideas in HighTechnology, co-ords. Don Nix and Rand Spiro, 163-205. Hillsdale, NJ:Lawrence Erlbaum.

Spiro, Emma and Andres Monroy-Hernández. 2016. “Shifting Stakes:Understanding the Dynamic Roles of Individuals and Organizationsin Social Media Protests.” PLoS One 11 (10): e0165387, 2016.

Stephens, Monica, and Ate Poorthuis. 2014. “Follow Thy Neighbor:Connecting the Social and the Spatial Networks on Twitter.”Computers, Evironment and Urban Systems 53: 87-95.

Theocharis, Yannis, Will Lowe, Jan Van Deth, and Gema García-Albacete.2015. Using Twitter to mobilize protest action: online mobilizationpatterns and action repertoires in the Occupy Wall Street,Indignados, and Aganaktismenoi movements. Information,Communication & Society 18 (2): 202-220.

Tilly, Charles, and Sidney Tarrow, Sidney. 2007. Contentious Politics.Boulder, CO: Paradigm Publishers.

Treré, Emiliano. 2015. Reclaiming, proclaiming, and maintaining collectiveidentity in the #YoSoy132 movement in Mexico: an examination ofdigital frontstage and backstage activism through social media andinstant messaging platforms. Information, Communication &Society 18 (8): 901-915.

259

Tremayne, Mark. 2014. “Anatomy of Protest in the Digital Era: A NetworkAnalysis of Twitter and Occupy Wall Street.” Social Movement Studies13 (1): 110-126.

Wang, Rong, Wenlin Liu, and Shuyang Gao. 2016. Hashtags andinformation virality in networked social movement: Examininghashtag co-occurrence patterns. Online Information Review 40 (7): 850-866.

Weffer, Laura. 2007. El socialismo necesita una hegemonía comunicacional.Entrevista a Andrés Izarra. http://venezuelareal.zoomblog.com/archivo/2007/01/08/entrevista-Andres-Izarra-considera-que.html(Accessed on April 2, 2015).

Xu, Weiai, I-Hsuan Chiu, Yixin Chen, and Tanuka Mukherjee. 2015. Twitterhashtags for health: applying network and content analyses tounderstand the health knowledge sharing in a Twitter-basedcommunity of practice. Quality & Quantity 49 (4): 1361-1380.


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