INVESTIGACIONES Y DOCUMENTOS Estudios sobre el Mensaje Periodístico ISSN-e: 1988-2696 https://dx.doi.org/10.5209/esmp.75758 #EsteVirusloParamosUnidos: Comunicación política de guerra en Twitter. Creación de comunidades homogéneas en la crisis de Covid-19 Anna Tous-Rovirosa1 y Daria Dergacheva2 Recibido: 29 de abril de 2021 / Aceptado: 28 de septiembre de 2021 Resumen. Se analiza la comunicación política en Twitter del Gobierno de España en el pico de la pandemia de Covid-19. La campaña en Twitter #EsteVirusloParamosUnidos fue monitorizada durante las fechas con los peores resultados en términos de fallecimientos (31 de marzo-4 de abril). La muestra incluye 398.523 tweets que se recogen en cuatro bases de datos. Mediante el análisis de redes sociales se identifican los principales actores y las interacciones entre los usuarios. Observamos una elevada coincidencia entre la tipología de portavoces de las ruedas de prensa institucionales y los principales actores del hashtag, dándose prioridad a la administración y a las fuerzas armadas españolas. Se observa también que los principales líderes de opinión se relacionaron con su esfera natural. Mediante el análisis computacional se concluye que en este hashtag se dio en un ambiente de guerra, que la palabra “gobierno” se mencionaba más que términos médicos, así como la presencia de términos militares. Palabras clave: Análisis de redes sociales; Twitter; comunicación política; covid-19; coronavirus; #estevirusloparamosunidos; cam- paña institucional; pandemia [en] #EsteVirusloParamosUnidos: War-like political communication on Twitter. Creating homogeneous communities in the Covid-19 crisis Abstract. This article analyzes the political communication on Twitter of the Government of Spain at the height of the Covid-19 pandemic. The #EsteVirusloParamosUnidos campaign on Twitter is monitored during the dates, with the worst results in terms of fatalities (March 31st– April 4th, 2020). In total, the sample included 398,523 tweets in four data sets. Through Social Network Analysis, the main actors and the main interactions between users were identified. The research shows a high coincidence between the typology of the press conference spokespersons and the main actors on the analyzed hashtag, prioritizing the Spanish administration and the armed forces. There was also a high relationship of the main opinion leaders with their “natural spectrum.” We conclude that in this hashtag, there was a “war-like” atmosphere. Via the computer-based text analysis, we identify that the word ‘government’ was mentioned more than medical words, and some military-like terms were present. Keywords: SNA; Twitter; political communication; Covid-19; coronavirus; #estevirusloparamosunidos; institutional campaign; pan- demics; Spain Summary. 1. Introduction. News and facts. Description of the situation 2. Press Conferences: Multiplicity of spokespersons 3. Literature review 4. Research Questions and Objectives 5. Method 6. Network Data Collection 7. Results 8. Discussion and Conclusions Cómo citar: Tous-Rovirosa, A., & Dergacheva, D. (2021). #EsteVirusloParamosUnidos: Comunicación política de guerra en Twitter. Creación de comunidades homogéneas en la crisis de Covid-19. Estudios sobre el Mensaje Periodístico 27 (4), 1227-1241. https:// dx.doi.org/10.5209/esmp.75758 1. Introduction. News and facts. Description of the with 950 deaths according to RTVE (2020) and based situation on the Spain’s Ministry of Health database. It has been one of the worst periods on record in Spain. Ac- The state of alarm in Spain began on March 14th, cording to the INE (Instituto Nacional de Estadísti- 2020, with the publication in the BOE (Boletín Ofi- ca/ National Statistics Institute), there were 23,778 cial del Estado/State Official Newsletter) of Royal deaths caused by Covid during March 2020, with an Decree 463/2020. At the time of writing this arti- additional 8,743 deaths with causes unidentified but cle, Pedro Sánchez’s executive had managed to ex- suspected of being caused by Covid for the same pe- tend the state of alarm for the fifth time until June riod. There were a further 38,325 deaths caused by 7th, 2020. In the period analyzed (March 31st-April Covid in April 2020, again with 17.134 not identified 4th), deaths from coronavirus totaled 5,216 in just five but suspected of being caused by Covid for the same days, with April 2nd being the worst day on record period (INE). 1 Universitat Autònoma de Barcelona (España) E-mail: anna.tous@uab.cat 2 Universitat Autònoma de Barcelona (España) E-mail: daria.dergacheva@autonoma.cat Estud. mensaje period. 27(4) 2021: 1227-1241 1227 1228 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 Recent studies have shown the preeminence of lution of the health crisis (El Confidencial, 2020b). traditional media (Casero-Ripollés, 2020), publicly The press conferences of the Technical Management owned (EBU, 2020) in media consumption as a re- Committee had five spokespersons. Some of them sult of the coronavirus pandemic. However, it is also had to be replaced because of the disease, such as highlighted that “the results suggest the existence of González and Ceña. A Ministry of Health represent- complementarity between traditional and digital me- ative, usually the director of the Center for Coordi- dia” (Casero-Ripollés, 2020: 11) in the hybrid com- nation of Health Alerts and Emergencies, Fernando munication model already described by Chadwick Simón; an armed forces representative (Chief of the (2013), as has been shown by Masip et al. (2020). Defense General Staff, Miguel Villarroya, or Chief of According to this research, digital media appears as Staff, Carlos Pérez), one of the Civil Guard (the dep- the first option to be informed (38.9%), followed by uty operational director, Laurentino Ceña and Gen- TV news (33.9%) and social media (11.4%). Infor- eral José Manuel Santiago); a representative from mation in digital media has been considered so im- the National Police (the deputy operational director portant that on April 18th, the European Commission of the National Police, José Ángel González and the adopted a recommendation on the use of digital me- commissioner, José García Molina, amongst others; dia as an important instrument for containment meas- and a transport spokeswoman (the ministry’s secre- ures (European Commission, 2020). Several studies tary-general, María José Rallo). have been focused on fake-news and disinformation The communication strategy of the Spanish in this pandemic (Andreu-Sánchez & Martín-Pas- government in this crisis has been widely seen as qual, 2020; Pérez et al. 2020; Salaverría et al., 2020). a failure. Principally, this is due to the multiplicity of stakeholders, which can lead to misunderstand- ings and lack of coordination (Camacho, 2020; Cos- 2. Press Conferences: Multiplicity of spokespersons ta-López, 2020; López-García, 2020), but also an ex- cess of appearances by the president, Pedro Sánchez, From mere observation, we can state that the Span- and the fact that most of the spokespersons are not ish government’s strategy was to appear on TV daily communication professionals. from the time the state of alarm was decreed. Such With the change of strategy, a high presence of the a strategy could have been a simple matter of keep- president is chosen, trying to reinforce his role as a ing the population informed. The president appeared leader (Camacho, 2020). According to López-García eight times, from March 12th until April 4th; the tech- (2020), the use of military personnel as spokesper- nical committee appeared 22 times (March 16-30th); sons could could signal a strategic appeal to these while several ministers appeared during the same stakeholders as they have a higher approval rating period, some 26 press conferences from March 15th within the general public’. until April 5th. In fact, all ministers have appeared in According to the CIS, in 2015, the Spanish gen- press conferences, except Irene Montero, due to her eral public’s approval rating of the Civil Guard was being quarantined. Costa-Sánchez and López-García (6,02), the National Police (5,95), and armed forces (2020) highlight that there have been several prob- (5,51). This was doubled that of their assessment of lems in the government’s political communication. the government (2,77), trade unions (2,61), and po- They focus on a lack of transparency, and they also litical parties (2,23) (CIS, 2015). López-García high- criticize the spokesperson formula adopted by the lights that this assessment remains on a similar foot- government, as it is contrary to the crisis commu- ing nowadays, so the “government sought to hide in nication recommendations. A multiplied spokesper- the military, police and Civil Guard” (López-García, son can be positive (as they take the initiative and 2020: 14). are proactive in the messages), but “it multiplies the Some scholars (Castelo-Szulman, 2020; López- risk of contradiction of the message and covers the García, 2020) and media have criticized the usage entire media space, saturates it, opening for the pub- of war metaphors (“against the coronavirus”) by lic a scenario of attention and permanent tension.” In the Spanish government spokespersons, particular- sum, according to these authors, the institutional ac- ly Pedro Sánchez. Susan Sontag already criticized tors “face the challenge of transparency, coherence, war metaphors against cancer in 1978 (Illness as a understanding with different stakeholders, leader- Metaphor) and against AIDS in 1988 (AIDS and its ship and disclosure (Costa-Sánchez & López-García, metaphors). The armed forces in Spain were used in 2020: 10-11). all kinds of tasks related to the Covid-19 crisis. So, A week after Santiago’s cessation because of his the fight against coronavirus was not just a metaphor. controversial statement that the Civil Guard was As López-García (2020: 9) states, “The war-like lan- working to reduce criticism against the government guage and the presence of uniforms on the news and (the Interior Minister, Fernando Grande Marlaska, in press conferences clearly showed intention from quickly stated that they were not acting against free- the government: this is a war.” Through this research, dom of expression), the Spanish government decided we will try to find out if this also happened in the to replace the press conferences that had taken place analyzed hashtag. with several spokespersons, some of them military. The government uses the Spanish Army’s Military They came out every morning to report on the evo- Emergency Unit to perform various functions related Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 1229 to the virus in what is called “Operation Balmis,” in Media is used to mobilize the bases, leading to dif- tribute to Francisco Javier de Balmis, the Spanish ferent movements between politics, media, and the military doctor that brought the smallpox vaccine to electorate. Social media are seen as a way to engage America and the Philippines. López-García (2020: 7) citizens and fight against political disaffection in con- emphasizes that media coverage of the UME (Span- temporary democracies because those who are polit- ish acronym for Military Emergencies Unit) was quite ically engaged on social media platforms tend to be positive. In fact, one of the few counter-reactions was more active (Jensen & Anstead, 2013: 162). Activism the opposition from the Catalan Government, which and new political parties have been widely studied at first refused UME’s help to undertake actions that, (Gibson, 2015; Linares, 2013; Pérez-Altable, 2015; according to them, could be perfectly realized by the García-Carretero & Díaz-Noci, 2018; Casero-Rip- Catalan administration (García, 2020). ollés, 2017; Valera-Ordaz & López-García, 2019). Social media in politics are being used to connect with young people (Utz, 2009), and to increase links 3. Literature review with the electorate, in a broad sense (Ward & Gib- son, 2008; Túñez & Sixto-García, 2011), as well as to In political communication, Social Media have been convey feelings (Coromina et al., 2018). According widely considered as instruments that facilitate ci- to some research, such as Kruikemeier’s (2014, 136), vilians to participate and become active political the use of Twitter in political campaigns is consid- subjects and empowered citizens (Casero-Ripollés, ered a positive input for political parties. 2017). The basis of this statement was clear: accord- More recent investigations show that political ing to the utopian point of view at the beginnings of communication on Twitter has developed an autoref- the research on the Internet (Meredith, 2013), the erential character (García-Ortega & Zugasti, 2018), Internet and Social Media would facilitate citizen’s as well as a lack of factual interaction with the elec- participation, and there were interesting problems to torate. Cifuentes and Pino’s (2018) results also led be studied, such as vulnerable populations (low ed- to the conclusion that political parties’ use of Twitter ucation and non-frequency of digital network use) was in relation to the creation of an “in-group” in Co- and their difficulty of equal access to these bene- lombia’s Democratic Center, via fostering cohesion fits (Casero-Ripollés, 2017). According to Cam- in the political party and with its electorate, mean- pos-Dominguez (2017), the analysis of Twitter as a while trying to attack their political rivals, placed in means of disseminating political messages is extraor- the “out-group” sphere. dinarily useful to get an overview of the discursive A variety of research has been undertaken, and strategies of any political party. in several areas, that we must quote here because There are multiple ways to study politics and so- of their proximity to the topic. To start, the use of cial networks: how social networks are integrated Twitter during the Covid-19 pandemic in Spain has into political campaigns (Householder & LaMarre, also been analyzed from a mathematical perspec- 2014), as well as the study by Kensi and Jomini tive (Gutiérrez et al., 2021). The authors analyze the (2006) on the relationship between Internet access, Twitter behavior of citizens and administrations dur- interest in political campaigns and national politics, ing states of alarm. and Twitter (Ausserhofer & Maireder, 2013); and The issue has also been analyzed with sentiment also political participation on Twitter (Bode & Dal- analysis techniques in several European countries rymple, 2014). Research into Spanish elections and (Kruspe et al., 2020) and via a topic modeling ap- social media has been undertaken by Baviera (2018) proach in order to explain which were the main top- and Guerrero-Solé (2018), amongst others. Guo et al. ics discussed on Twitter during the pandemic (Agüe- (2020) have recently analyzed the 2016 US elections ro-Torales et al., 2021). Finally, the authors of this and the effects of Twitter’s echo chamber. Ausser- paper have also analyzed war-like language in the hofer and Maireder’s research concluded that the net- hashtag #estevirusloparamosunidos (Mustajoki et al., work formed by Austria’s most political Twitter users 2020). was dominated by a political professional elite but Social networks do have a process of constant was open to outside participation. The topic analysis negotiation “to impose a certain story” (Coromina, reveals the emergence of niche authorities and the pe- 2017). It is good to bear in mind that in a crisis such as riodic divergence of the political discourse on Twitter this, the administration may have not only this need with that of mass media (Ausserhofer & Maireder, to impose a particular story in the hashtag analyzed 2013: 291). Social Media as an implement used by but also an additional narrative. Furthermore, social political communication has been analyzed in the platforms have been studied as spaces where affini- context of fragmentation and segmentation (Gibson, ties and similar points of view between users led to 2015: 184). In a broad sense, media space has evolved filter bubbles (Pariser, 2011) or echo chambers where from a ‘one size fits all’ logic to a segmented appeal users are only exposed to agreeable opinions, without (Gibson, 2015: 184), or, in Negroponte’s words, from forgetting the importance of a platform’s algorithms “prime-time” to my time (Negroponte, 1994). to ensure the permanence of the users on the page Another interesting issue is activism. As Castells (Baeza-Yates, Peiró, 2019). “As a result, we may see (2013) pointed out, in relation to politics, Social increasing social fragmentation and ideological po- 1230 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 larization in our society” (Liao and Fu, 2014: 2745). Nowadays, it is not at all rare that a public ad- The echo chamber effect has been studied by Colle- ministration creates a hashtag on Twitter related to a oni et al., 2014; Freelon et al., 2015; Himbelboim et campaign created and developed to sensitize the gen- al., 2013; Guo et al., 2020; Liao and Fu, 2014; and eral public and raise awareness of the difficulties and Johansson, 2018, amongst others. Echo chambers recommendations to overcome the health crisis. The in Twitter also have their detractors, as indicated in institutional campaign #EsteVirusloParamosUnidos the title “Twitter Is Not the Echo Chamber We Think started with a press campaign: the most important It Is” (Shore et al., 2018). But the more generalized legacy media in Spain (El País, El Mundo, ABC, La perspective is that Twitter as a Social Media plat- Razón, La Vanguardia, El Periódico, amongst others) form reproduces the effect, which tends to increase appeared on March 15th, 2020, with the same cover polarization, as “people tend to discuss issues only and the hashtag of the campaign. Some legacy media with other like-minded people” (Du, Gregory, 2017). from other countries in South America imitated the There are several research scholars studying the echo press campaign, such as Puerto Rico (El Confiden- chamber effect on Twitter, either in terms of racism cial, 2020a), Argentina, México, and Perú (Lubianco, (Criss et al., 2021), the Covid vaccination (Cossard et 2020). al., 2020), or the Greek Referendum and Europe as a The campaign has been released by the Spanish public space (Michailidou, 2017), to name but a few. Ministry of Health Sanitary Spanish Ministry and Therefore, we consider that the echo chamber has been created by the Spanish advertising agency effect and polarization should be related to the us- Kitchen. It was dealt with urgently, under Article 16, age of Twitter by politicians and political institu- Royal Decree Law 7/2020 (March 12th). According to tions, because according to several research studies, El Confidencial Digital (2020) and Dircomfidencial they usually employed Twitter for campaigning, for (27/3/2020), the cost of the media buying campaign self-promotion and to spread information rather than was 4.5 million euros and was the most important to engage in conversations, even though Grant et al. campaign in Spain during March 2020. Amongst (2010:579) showed that those who did interact with other institutional campaigns, it was also the subject other users appeared ‘to gain more political bene- of questions to the government by the opposition fit from the platform than others’ (Ausserhofer and (PP/ Partido Popular) in relation to the awarding of Maireder, 2013: 292). In this sense, Guo, Rohde, and institutional advertising campaigns. (EuropaPress, Wu’s (2020: 234) study concluded that “certain opin- 2020). The campaign #estevirusloparamosunidos has ion leaders were responsible for creating homogene- a digital aspect, including a website (Ministerio de ous communities on Twitter.” Sanidad, 2020), Facebook (Ministerio de Cultura y Towers et al. (2015) studied Twitter’s repercus- Deporte, 2020), Telegram, banners, a YouTube vid- sion in the US’s Ebola health crisis; Vijaykumar et al. eo, and the hashtag on Twitter, as well as a tradition- (2018) analyzed information about Zika in Twitter, al one comprising media, cradle, and posters. As of also in the US, and they considered that the spread May 22nd, 2020, Telegram and Twitter have the best of information in Twitter had been positive: “As this results in terms of quantity of users engaging with the study illustrates, journalists and news media organ- campaign. izations play a significant role in disseminating and amplifying Emerging Infectious Disease Outbreak (EIDO) information, with much of the Twitter con- Table 1. Number of views and likes tent related to public health updates, actions, and of the official social network channels of campaign advice” (Vijaykumar, 2018: 555). Some researchers #EsteVirusLoParamosUnidos highlight that Twitter does have a preeminence on in- Social Network Visits/ Subscriptors* Likes formation distribution related to health (Bakal & Ka- Facebook 14.000 268 vuluru, 2017), but, along with some other problems observed in other social media, there is a dangerous Youtube video 1,516,021 2.5K mixture of information, easy and quick distribution, Telegram 3.414.000 Does not apply and the lack of verification (Albalawi et al., 2019; Perez et al., 2020: 4). Twitter over 3.000.000 of tweets Does not apply Political communication has been following sev- *Spanish Ministry Official Telegram channel eral novelties related to the Internet and new social media and using them to improve communication with the general public (Túñez & Sixto, 2011; Cam- 4. Research Questions and Objectives pos-Dominguez, 2017). In fact, some authors claim These are the research questions that we will try to the leadership of political class in the usage of new answer in this paper by analyzing the hashtag #es- technologies (Guerrero-Solé and Mas-Manchón, tevirusloparamosunidos during the aforementioned 2017). According to López-García (2017), Twitter period. undoubtedly constitutes one of the social networks RQ1: Who were the opinion leaders in the cover- best adapted to the nature of political communica- age of the pandemic? tion, which is the interrelation between three actors RQ2: What is the typology of the main actors on (politicians, media, and citizens) in the same space. Twitter? Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 1231 RQ3: Who are the main Twitter users disseminat- sites (e.g., among the latest – Mercea et al.: 2020; ing the information in the ego networks of the most Pavan: 2020). important actors in this campaign on Twitter? Using SNA techniques, the main objective of this research is to analyze and visualize which network is 6. Network Data collection woven inside the hashtag #estevirusloparamosunidos circulating on Twitter around the Covid-19 pandem- The data was collected from Twitter from March 21st, ic. 2020 – April 20th, 2020. Twitter’s followers’ network The specific objectives are the following: is a directed graph where nonreciprocal relations are permitted (Morales et al., 2014). All publicly availa- 1. To identify the main actors. Find out which ble tweets with the hashtag #estevirusloparamosuni- are the users that have relevance or authority dos were collected. Overall, 1,232,759 tweets were 2. To study which are the main interactions in collected over the period of 31 days. We took a sam- the network. ple of tweets for the week when the pandemic was 3. To observe whether there are any coinci- peaking. As the worst day of the pandemic in Spain, dences between the spokesperson(s) at press in terms of deaths from Covid-19, was April 2nd, we conferences and the spokesperson(s) at the chose the sample of tweets from the week of March space created on Twitter. 31st – April 4th. The sample included 398,523 tweets. They were analyzed via social network analysis first as name networks for each day of the peak. The name 5. Method network analysis studies the messages’ content and connecting nodes (in our case – Twitter users) be- This study examined the Twitter hashtag #estevirus- tween each other in case they reply, repost, or men- loparamosunidos during the peak of the coronavirus tion another user’s tweet (Gruzd: 2009). A Twitter pandemic in Spain. The analyzes were based on four actor, or name, network shows us who interacts with data sets of publicly available tweets with the hashtag whom in relation to a hashtag or search term (Gra- collected during the dates March 31st – April 4th, 2020. ham and Ackland: 2017). The total sample included 398,523 tweets in four data The resulting Name Networks were exported to sets. Through Netlytic software and ORA software, ORA software in GraphML format, a network visual- we created a Social Network Analysis and comput- ization application (Gruzd, Haythornthwaite: 2013). er-based text analysis of the tweets from March 31st We then created a dynamic network that showed – April 4th, 2020. This computer-based text analysis how the main actors’ posting behavior and impor- records the word frequencies during these dates in tance for the network (centrality measures) had the campaign #estevirusloparamosunidos. changed during this period. This dynamic network On Twitter, Netlytic is widely used to study hash- had 21,397 nodes, meaning that the total number of tag campaigns, political activism, and political com- Twitter posters connected to each other in a network munication. Some of the latest examples include an during this week was 21.397. As there were a great analysis of feminist identity by Lommel et al. (2019) deal more tweets, it means that some actors had post- through research on the international hashtag cam- ed far more than once or twice. In fact, some of them paign #DayWithoutAWoman; Romeiro et al. (2021) had posted hundreds of tweets. analyzing a protest campaign by the opposition in For the purpose of analysis, the four input me- Brazil during Covid-19 with a hashtag #Somos70por- ta-networks were divided into three periods: Begin- cento; and Figueiredo (2021) studying #dia26euvou ning (March 31st), Middle (April 1st-2nd), End (April in Brasil which deconstructed the left-wing protest 3rd-4th). movement narrative. ORA is software included in Some nodes were excluded as they represented Sage’s handbook on Social Network Analysis (Scott a part of another hashtag, for instance, SEGUIMOS & Carrington, 2014). It is commonly used by stud- LUCHANDO JUNT@S ies in political communication and social networking 1232 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 7. Results Table 2. Twitter accounts of the opinion leaders that appeared most frequently in multidimensional network built on the hashtag #estevirusloparamosunidos (March 31th – April 4th 2020) # Beginning Value # Middle Value # End Value 1 sanidadgob 0,110 1 antobald98 0,065 1 sanidadgob 0,148 2 sanchezcastejon 0,106 2 sanidadgob 0,054 2 mercadona 0,054 3 mitmagob 0,088 3 sanduhadah 0,024 3 ejercitoaire 0,046 4 guardiacivil 0,047 4 tc_disisleri 0,024 4 salvadorilla 0,040 5 policia 0,044 5 tcsavunma 0,024 5 elprogramadear 0,037 6 ejercitotierra 0,035 6 tcbestepe 0,024 6 guardiacivil 0,034 7 ejercitoaire 0,034 7 mercadona 0,023 7 defensagob 0,028 8 umegob 0,030 8 camillebertrand 0,021 8 sanchezcastejon 0,027 9 sevillafc 0,024 9 brandspain 0,020 9 mitmagob 0,026 10 nato 0,022 10 dani78175141 0,018 10 feriademadrid 0,025 11 diba 0,022 11 jaarcossanchez 0,016 11 policia 0,024 12 laliga 0,021 12 mossos 0,16 12 valenciacf 0,023 13 proteccioncivil 0,020 13 barcelona_gub 0,16 13 24h_tve 0,023 14 maecgob 0,018 14 embespturquia 0,16 14 rccelta 0,022 15 mjmonteroc 0,017 15 mevlutcavusoglu 0,16 15 aspas10 0,021 16 yosoy8a 0,016 16 eldiarioes 0,16 16 populares 0,020 Source: Own elaboration RQ1 asked who the opinion leaders were in the To better understand the composition of the coverage of the pandemic. network based on the hashtag #esteviruslopara- Table 2 presents opinion leaders that appeared most mosunidos, we also visualized and analyzed the frequently on Twitter in each period. To measure a Twitter network in Netlytic, using three periods Twitter user’s influence in a network, we used in-degree of collection. Because the networks are very centrality. The in-degree centrality defines how many large, and constitute around 100,000 tweets for network ties were pointed towards a user (Borgatti & each period, only the largest connected clusters Everett: 2018). Researchers previously defined opinion (components) were displayed, while isolated leaders as having an in-degree centrality of at least 10% nodes and small disconnected clusters were not (Valente and Pumpuang, 2007). This research uses the taken into account (Gruzd & Tsyganova, 2014). 2% threshold because of the large scale of the Twitter Each of the five clusters of each period was thus networks analyzed, and as suggested by previous Twit- visualized, and based on the visual examination, ter research (Guo et al., 2018), this could ensure that the main actors were identified. The visualization the study detects a broad range of users. A total of 38 was done day by day. unique opinion leaders were identified. The analysis of They represent the most important nodes in a con- in-degree centrality was carried out on the whole net- crete visible cluster that Netlytic identified. As can be work over all the actors who had in-degree over 2%. So, observed, the most repeated ones in Table 2, during some were added in periods 1 and 3, and some were de- the three periods, are sanidadgob; sanchezcastejon; leted in period 2, for instance, because they didn’t pass mitmagob; guardiacivil; ejercitoaire, and mercadona. the threshold. All in all, there are those Twitter users It can be noted in the following graphs (See also Ta- – opinion leaders, who passed a 0.02 threshold accord- ble 3) that these were the main stakeholders during ing to the in-degree centrality. the peak of the pandemic. Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 1233 Figure 1. March 31st. All clusters Figure 2. April 1st-2nd. All clusters Figure 3. April 2nd-4th. All Clusters RQ2 was about the typology of the main actors of gy. The main categorization is between politicians, the hashtag. We categorized the main actors (those administration and institutions, and other social ac- with the highest in-degree centrality of the network tors, which we are not mentioning further, such as over time). The following table presents the typolo- sportsmen, influencers, businesses, and the like. 1234 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 Table 3. Politicians, administration and institutions’ Twitter accounts that appeared most frequently on Twitter during the period of data collection of multidimensional network built on the hashtag #estevirusloparamosunidos (March 31th – April 4th 2020) International Other Political Spanish Government Armed Forces Spanish Administration Bodies Governments parties Sanidadgob - Ministerio de Sa- nidad (Ministry of Health) Guardia Civil diba - Diputació de Barcelona (Barcelona Provincial Coun- cil) nato - Official Twitter account of NATO - the North Atlantic Treaty Organization tc_disisleri - Ministry of Fore- ign Affairs of Turkey tcsavunma Republic of Turkey Ministry of National Defence tcbestepe –administration of the President of Turkey @populares – Partido Popular Mitmagob - Ministerio de Transportes, Movilidad y Agenda Urbana, Gobierno de España. Ministry of Transport, Mobili- ty and Urban Development Policia- Police sanchezcastejon Pedro Sán- chez, Presidente del Gobierno de #España. President of the Spanish gover- nment, Pedro Sanches Ejercitotierra – the Spanish army Salvador Illa Roca - Ministro de Ministerio de Sanidad Head of the Health Ministry of Spain Ejercitoaire – the Spanish Air force umegob - Unidad Militar de Emergencias Military Emergencies Unit Source: Own RQ3 tried to answer which are the main Twitter From the main actors of the Netlytic visibly identi- users disseminating the information in the ego net- fied clusters, five ego-networks of this particular cam- works of the most important actors in this campaign paign were analyzed, the prerequisite being that they on Twitter were the central actor in a cluster at some point in time. As Everett and Bogartti (2005: 32) pointed out, As stated before, the main actors identified through vis- “ego networks are drawn from the same basic net- ualization and in-degree centrality were: sanidadgob; work, and the objective is to give a network measure sanchezcastejon; mitmagob; guardiacivil; ejercitoaire of importance to enable us to compare the central- and mercadona. As there is a majority of institutional ities of the egos in our sample.” For the purpose of and political actors, we decided to focus on these and this research, we take the definition of ego networks leave aside the commercial Twitter account (mercado- by Bogatti et al. (2005). Perhaps a more simplistic na), which we have categorized as “other social actors.” phrasing: Ego-networks consist of a single actor We can observe which was the ego-network and (ego), the actors connected to it (alters), and all the betweenness of these five main actors. Below are the links between them. graphs for the president of the government, Pedro Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 1235 Sánchez; the rest can be found in the appendices. The also enabled us to identify the main actors inside each information that we can visualize in these graphs has ego-network. Graph 1. Ego-network of the president of the Spanish government, Pedro Sánchez Table 4 Red Highest Orange Intermediate Yellow Medium-level Green Low Blue Lowest In particular, we paid specific attention to the @KilianCD; @Perona10690463; @937908Mcm; @ betweenness centrality in these ego-networks. Be- AlegraAlonso; @nusagatero) are present not only tweenness studies the extent to which an actor is be- in one ego-network but several. Moreover, Social- tween all other actors within the network (Borgatti & ist Party members or supporters are present in every Everett, 2005), and the more central it is, the more ego-network´s top betweenness centrality actors. important for information dissemination the actor Betweenness centrality in ego-networks of the would be. Betweenness centrality identifies individ- main actors of the multidimensional network built on uals or organizations that are potentially influential the hashtag #EsteVirusloParamosUnidos (March 31st and are positioned to impose connections between – April 4th)[1] groups and to bring to bear the influence of one group [DD2] [DD3] As it is visible from the table and on another or serve as a gatekeeper between groups the node clouds, the majority of actors important for (Carey, 2014). the dissemination of information in the ego-networks As with the in-degree centrality typology, we of most important speakers of the campaign, are pol- read through Twitter profiles and available tweets iticians from the Socialist Party or government or- and identified the main ten actors with the highest ganizations. betweenness centrality in these five ego-networks Below are the node clouds of the ego-networks (excluding egos themselves). of Pedro Sánchez, as one of the most important ac- In many cases, we have found that the users that tors in this campaign. The other most important ac- constitute the most important actors in terms of be- tors’ clouds can be checked in Appendices. They are tweenness centrality in our five ego-networks are the colored according to betweenness centrality, with same individuals or institutions and mostly from the red being the highest. As it is visible from the node socialist political spectrum. For instance, Twitter ac- clouds, the previous conclusions about main actors counts of the same Socialist Party supporters, as re- supporting the opinion leaders are, in many cases, corded in their Twitter accounts (@Teresaperezcep1; Twitter profiles of either members of the Socialist 1236 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 Party or government/military organizations. As for stands for the highest betweenness centrality, and the ego-network’s color code, for node clouds, red blue stands for the lowest betweenness centrality. Table 5 Betweenness Centrality in Ego Networks of the main actors of multidimensional network built on the hashtag #estevirusloparamosunidos (March 31th – April 4th 2020) Socialist party members or Government organization/ Whose network Others supporters military President of the Spanish government, Pedro Sánchez 9 0 0 Sanitary Spanish Ministry 7 1 1 Spanish Army 3 3 3 Spanish Air Force 2 7 0 Spanish Guardia Civil 3 2 4 Source: Own elaboration Graph 2. Node cloud of the ego-network of the president of the Spanish government, Pedro Sánchez Computer-based text analysis (39,4675 mentions vs. 398,523) because the compu- tational text analysis did not consider the same hash- The following section describes is the comput- tag written with emojis, for example. What is visible er-based text analysis of the word frequencies from from the twenty most mentioned words is that the March 31st – April 4th, 2020 in the campaign #Es- word ‘government’ was mentioned far than medical teVirusloParamosUnidos. Through Netlytic soft- words (such as ‘sanitario’ or ‘sanidadgob’) and that ware, we made a computer-based text analysis of the some military-style terms are present, such as ‘lucha’ tweets from March 31st-April 4th, 2020. We removed (fight) and ‘alarma’ (alarm), as well as administrative the ‘meaningless’ words such as verbs, pronouns, and words ‘medidas’ (measures). The words related to some common nouns such as “días” or “marzo.” The health and sanitary issues such as ‘esenciales,’ ‘tra- most mentioned hashtag, #EsteVirusloParamosUni- bajadores’ (essential workers), and ‘actividades’ (ac- dos, has fewer mentions than tweets for this period tivities) are at the very end of this list. Table 6. The most mentioned words and hashtags in the texts of tweets of corpus built on the hashtag #estevirusloparamosunidos (March 31th – April 4th 2020) # Word in Spanish English translation Number of mentions 1 #estevirusloparamosunidos hashtag: “we will stop this virus together” 394.675 2 #covid19 hashtag “covid19” 85.635 3 Gracias thank you 39.939 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 1237 # Word in Spanish English translation Number of mentions 4 España Spain 36.402 5 Gobierno Government 33.407 6 Medidas Measures 30.223 7 #quédateencasa hashtag: “stay at home” 24.566 8 Sanitario Sanitary 23.165 9 Casa Home 20.360 10 Personas Persons 19.470 11 Crisis Crisis 12.987 12 Alarma Alarm 12 560 13 #coronavirus hashtag “coronavirus” 12.354 14 Material Material 12.128 15 Lucha Fight 11.631 16 @sanidadgob Twitter account of the ministry of health 11.231 17 Esenciales Essential 10.338 18 Trabajadores Workers 9.718 19 Actividades Activities 9.670 20 Compañeros Fellows 8.034 8. Discussion and Conclusions tions– particularly not as personal Twitter accounts. Neither the majority of ministers (with the exception Besides having answered the research questions, of the Ministry of Health, Salvador Illa, and mitma- there have been some topics that emerged thanks gob) nor the majority of military personell. Instead, to this research. We can see there is a high level of there is a huge leadership of the aforementioned of- coincidence between the typology of main actors in ficial accounts representing the same social and in- press conferences (which were broadcast by TVE stitutional stakeholders. So, this is a sphere that may and almost all generalist channels at that time) and be open to outside participation, but, in fact, it only in the hashtag analyzed, as the communication strat- attracts similar actors. This could be studied in fur- egy from the Spanish government consisted clearly ther research analyzing its political homophily (Guo of prioritizing the armed forces (guardiacivil, ejer- et al., 2020). It is also interesting to realize that Pe- citoaire) in addition to the Spanish administration dro Sánchez and Salvador Illa have more socialist (sanidadgob, sanchezcastejon, mitmagob). We have individuals supporting them in the dissemination of to bear in mind that the analyzed hashtag belongs to information, whilst the military has fewer. We have a wider institutional campaign, #estevirusloparamo- observed that there is a high relationship between sunidos, whose aim was to sensitize the citizens. As politicians and militaries in this hashtag, but each of stated previously, the computer-based text analysis them remains to have their own “circle.” It is also reinforces these results, along the lines that the em- important to highlight that ejercitoaire, ejercitotierra, phasis was placed on administration and war-like and guardiacivil did share “saludpublica,” as we can language above the health and sanitary issues. observe in the ego-network’s clouds. It is fairly clear that the main opinion leaders had In this sense, we point out that the behavior ob- a strong relationship with their “natural spectrum.” served in the social networks analyzed coincides with The results show us that, due to fragmentation and social fragmentation (Liao and Fu, 2014) and homo- segmentation, this is not only a “segmented appeal” geneous communities (Guo et al., 2020) and could (Gibson, 2015: 184). We are not exactly talking about lead to the so-called echo chambers and polarization. an “elite” of main opinion leaders, but a fairly closed Therefore social networks, in this case, Twitter, would group (niche) that particularly interacts with its nat- reach the opposite objective to that which the Inter- ural common sphere, with few exceptions (Partido net was supposed to produce in its beginnings (Mere- Popular in Table 1, position 16th, last period analyz- dith, 2013) and, of course, the opposite objective that ed). the government administration should pursue with It is also an interesting finding that several of the its communication with citizens through institution- spokespersons in press conferences do not appear as al campaigns. The results of our research are fully in relevant actors of these networks inside the top posi- line with other research on polarization, as they reach 1238 Tous-Rovirosa, A., & Dergacheva, D. Estud. mensaje period. 27(4) 2021: 1227-1241 similar conclusions about homogeneous communities We can also conclude that the network analyzed (Gutiérrez et al., 2021). On the other hand, topic-mod- has an autoreferential character (García-Ortega & eling research concludes that, during the lockdown, Zugasti, 2018), as the main opinion leaders keep in- users focused on “the Spanish emergency, considered teracting with citizens that are particularly politically health and economic problems,” meanwhile at the aligned to the socialists; furthermore, because of the pre-crisis stage, they focused on the international pan- “behavior” of its main opinion leaders, as they inter- orama (Agüero-Torales et al., 2021, 186). Although it act especially with themselves and with related polit- is not possible to compare results, due to their method- ical actors. 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Virtual Zika transmission after the first U.S. case: Who said what and how it spread on Twitter. American journal of infection control, 46(5), 549-557. https://doi.org/10.1016/j. ajic.2017.10.015 Ward, S., & Gibson, R. (2008). European political organizations and the Internet. In: Chadwick, A., Howard, P. N., (Eds.), Routledge handbook of Internet politics, (pp. 25-39). Routledge. https://doi.org/10.4324/9780203962541 Anna Tous-Rovirosa. Associate professor at Journalism and Communication Sciences at UAB (Bellaterra, Spain). Doctor from the same University, her PhD was awarded by the Catalan Audiovisual Council (CAC). She has been a visiting scholar in the universities of Salvador de Bahia (Brazil), Bochum (Germany) and East Anglia (Norwich, UK). Her research topics are online journalism, interactivity and TV studies. The results of their research are available at books and international journals such as Journal of Spanish Cultural Studies, El profesional de la información and Palabra Clave, amongst others. ORCID: http://orcid.org/0000-0003-4519- 3793 Dr. Daria Dergacheva has just defended her PhD dissertation with distinction at the Autonomous University of Barcelona. She received a Chevening scholarship and graduated from the School of Media at the University of Westminster in 2013. Before that, she worked in the Russian media for over 10 years. She has published in international journals such as Russian Journal of Communication and Quaestio Rossica, amongst others. OR- CID: http://orcid.org/0000-0001-8773-7934