A Network Based Approach to Characterize Twenty-First-Century Populism in Colombia
AA Network Based Approach to CharacterizeTwenty-First-Century Populism in Colombia
Juan D. Garcia-Arteaga a , Valentina Pellegrino b a School of Medicine,Universidad Nacional de Colombia,Bogot´a, Colombia b LASC: Laboratory for the Anthroplogy of the State in Colombia,Bogot´a, Colombia
Abstract
Populism is a political phenomenon of democratic illiberalism centered on thefigure of a strong leader. By modeling person/node connections of promi-nent figures of the recent Colombian political landscape we map, quantify,and analyze the position and influence of Alvaro Uribe as a populist leader.We found that Uribe is a central hub in the political alliances networks, cut-ting through traditional party alliances, but is not the most central figure inthe state machinery. The article first presents the framing of the problem,followed by the historical context of the case in study, the methodology em-ployed and data collection, analysis, conclusions and further research paths.This study has implications for offering a new way of applying quantitativemethods to the studies of populist regimes.
Keywords:
Populism, Political, Networks, Colombia
1. Introduction
Populism is a phenomenon broadly defined as the pursuit of politicialpower by use of a confontational narrative founded on the concept of “us,the people” against “them, the elite”. Once considered a result of polit-cally immature systems, the rise of populist figures in well established liberaldemocracies in Europe and North America[39] has renewed interest in the
Email address: [email protected] (Juan D. Garcia-Arteaga) a r X i v : . [ c s . S I] F e b ubject and in understanding how and why these regimes come to power[15][32].Although populist focused studies date back to the 1960’s, there is stillnot a consensus on whether populism should be defined as a communicationstyle, an ideology or a political strategy. The research question in contempo-rary studies has then shifted from what populism is to how may populism bequantified. Recently the field has added studies about the degree of populismin specific contexts, recurring to textual and content analysis of discourses,speeches or manifestos [26][31][41][42]. Additionally, there has been an in-crease in the studies of the attitudes in citizens that can be supportive ofpopulist regimes [10] [1] [44] [28].These studies are valuable as there is much gain in understanding thediscourse patterns of populist leaders and how masses are incorporated intothem. However, these approaches tend to ignore both the impact of populismin the party system [27] and, more generally, how populists leaders fit in inthe landscape of political power relationships. It is possible that, by centeringin the figure of the leader and his or her discourse, we are falling into thetrap of methodological individualism denounced by [49]: a tendency to focuson individuals instead of relationships, which entails unrealistic assumptionsof the independence of these individuals.In this article we present an alternative to a widespread tendency to studypopulism and the networks that support it separately [43]. Specifically, wewill analyze the network of political alliances and work relationships sur-rounding a populist leader: Colombia’s former president Alvaro Uribe whoseongoing influence and politics have been used as an example of neo-populismby various authors [37, 20].We offer a novel analysis based on the Colombian political networks toshow how Uribe has a central role in them, contesting the commonly heldbelief of the source of populist power being the direct contact of the leaderwith the masses without the mediation of traditional political machinery.Our research is based on publicly available profiles documenting differentrelationships types such as political alliances, work relationships, rivalriesand family ties of the main actors of Colombian politics.The article is organized as follows. In the rest of the Introduction weprovide a general context of Colombian politics in the last two decades andbriefly review the use of networks in the analysis of political problems. Wethen describe the dataset used to capture the relationships between differentactor of the Colombian political scene. The data collected is then analyzed2sing well known concepts of network analysis such as centrality and com-munity detection. We show how these concepts relate to political strategiesput in place to consolidate power. A former congressman, Governor and Mayor of Medell´ın, Alvaro Uribedistanced himself from the Liberal Party because of his hard-line securitypolitics. Running as an independent in the 2002 presidential elections andwinning by a landslide, Uribe became the first president in Colombian his-tory outside of the traditional two-party system. Once in office, he used hisimmense popularity and political influence to change the constitution and re-move the ban on presidential reelection, thus allowing himself to be reelectedfor a second term (2006-2010).Unable to run for a third term, Uribe supported the candidacy of JuanManuel Santos, his former minister of Defense and assumed ally. Santoswas elected for the 2010-2014 term by cashing in Uribe’s electoral force andwas re-elected for the 2014-2018 term on a completely different platformbased on signing a peace treaty with FARC guerrilas. Uribe then becamethe most vocal and visible opponent to the peace project and to the Santosadministration, creating a right wing opposition party,
Centro Democr´atico (Democratic Center, hereafter CD), and being elected as a Senator in theColombian Congress twice (2014-2018 and 2018-2022).The CD now constitutes the majority of the Congress. Colombia’s currentpresident (Iv´an Duque, 2018-2022) belongs to the CD and was elected underthe strong support and campaigning of Uribe.Uribe is one of the most interesting examples of neo-populism as, on theone hand, he and his communcation style fulfill the commonly accepted char-acteristics of a populist leader: charismatic, mobilizes masses appealing to adirect communication style, presents himself as an outsider of the traditionalpolitics, promotes an “us against them” adversarial politics that minimizesthe space for democratic deliberation, and promotes the idea of his manifestdestiny as the only possible “saviour” of the country from its perceived ene-mies. On the other hand, his status as populist has been challenged mainlybecause his origins are strongly rooted in the traditional Colombian eco-nomic and political elite, undermining the “people vs the elites” oppositionthat characterizes many populist regimes.3 .2. Individual Power Networks
There is a widespread structuralist approach in the social sciences whichdefines power as relational rather than inherent to the agent [33], i.e. actor A ’s power is defined in relation to his influence over actor B . Political sciencemay then be seen as the study of the relationships that create, access, use,accumulate and/or preserve power within a society and politics themselvesmay be understood fundamentally as a network phenomenon[35]. This rela-tional approach is slowly gaining foothold in a discipline mostly grounded ontheories that assume independence of actors.The use of networks as an adaptable tool to describe various relationshipsbetween individuals, as opposed to other collective actors such as states orpolitical parties, has been adopted by various researchers to describe politicaldata[50][33]. An important part of this research is based on the analysis ofdigital data from social networks and focuses on individuals and potentialvoters. The relatively immediate availability of this type of data has pro-moted a large corpus of research describing the formation of communitieswith similar political points of view, the relationship between political leaderand their followers and predicting the political alignment of potential voters[13, 12].The research of networks the inner structures of power wielding politicalinstituions are rarer, possibly due to the difficulty of accessing descriptivedata [45]. In some cases, relational data may be manually collected frompublic information [36, 23] or from direct surveys [4, 29], but the process iswork intensive, slow and difficult to keep up to date [47].Affiliation networks [7, 34], bipartite graphs in which one set correspondsto individuals and the other to groups to which the individuals belong, havebeen used as an alternative to direct relationships. When available, it ispossible to use groups corresponding to formal and well defined affiliations, e.g. families [14] or political parties [18]. In other cases, especially in politicalsystems without a strong culture of information openness, authors have touse more flexible relation definitions to build the networks, e.g. alumni-connections of US congressmen [5] or intelligence reports of the simultaneouspresence in public events of Soviet Politicians during the Breshnev era [17].Relationships between members of deliberative assemblies, such as parlia-ments and legislative bodies, may be uncovered by analyzing the coincidencesof their voting pattern in support of bills [46, 40, 21].In the following Section we will describe a semi-automatic method to4 igure 1: Number of edges per relationship type. collect direct relational data (“works with”, “is allied with”) of prominentfigures of recent Colombian history.
2. Data
Data was collected from the “Quien es quien” (“Who is Who”) sectionof “La Silla Vacia” (“The Empty Chair”), an independent Colombian newsand political journalism website using web scrapping tools implemented inthe Python 3 programming language [48]. The raw data consisted on 344individual profiles saved as plain html text webpages.The webpage of each person in the network includes a brief profile andhyperlinks to related profiles. There are five types of relationships betweenprofiles: Work, alliance, friendship, family and rivalry. These relationshipsare, in general, non-exclusive, meaning two nodes may be related by morethan one type of edge. The total number of edges by relationship type ispresented in Figure 1.It is clear from the figure that the most common type of relationship is“Work”, with more edges (783) than all the other edge types combined (613),followed by “Alliance” (381). Although all edge information could be repre-sented either by a multiplex network, i.e. one in which each individual/node http://lasillavacia.com/quienesquien igure 2: Number of nodes in the largest connected component per relationship typegraph. is connected by different edge/relationships [8], the difference in size wouldbias results towards “Work”, the most populated edge type.We have opted instead to analyze separately only the “Work” networkand “Alliance” networks (hereafter WN and AN, respectively) as they arethe only edge types with a significant number of edges with respect to thenumber of nodes. Additionally, in both of the chosen networks there is agiant connected component (one in which a path exists between any pair ofnodes) connecting more than half of the networks elements (Figure 2).
3. Analysis
Figure 3 shows the normalized frequencies of node degree (number ofedges connected to each vertex) of WN and AN. Both networks show a verylong-tail and nodes with degrees an order of magnitude above the average,characteristics of power law distributions [11, 25].Formally, a distribution is said to follow a power law if the fraction ofnodes of degree k is proportional to an exponential function: P ( k ) ∼ k − γ . (1)Instances of natural, social and man-made networks spontaneously show-ing this behaviour have been extensively reported in the literature[11].6 igure 3: Frequecies of node degrees for AN (left) and WN (right). The fitted power lawcurves using γ values of 0 .
95 for AN and 0 .
85 for WN are overlain. Bottom row show thegraphics in a logarithmic scale.
Although there is still no consensus over the exact mechanisms whichresult in this type of distribution, preferential attachment, also referred toas a “Yule Process”[52] or “the rich get richer effect”, has been proposed asa possible explanation. In this type of processes, new edges added to thenetwork by a random or partly random process will attach with a higherprobability to nodes with higher degrees in a self reinforcing loop[2].
A widely accepted, although loose, definition of a node’s centrality comingfrom the study of social networks and organizations states that centrality isrelated to the “importance” of the node within the graph [22]. The mostcentral nodes of AN and WN networks were calculated using four commonmeasures: Degree, Betweenness, Closeness and Eigenvector Centrality. Byall four metrics Alvaro Uribe is the most central node of the AN and formerPresident Juan Manuel Santos the most central node of the WN network.Results are shown in Table 1. 7lliance NetworkDegree Betweenness Closeness EigencentralityAU 31 AU 0.387 AU 0.378 AU 0.288GV 19 EP 0.187 EP 0.376 EP 0.276Work NetworkDegree Betweenness Closeness EigencentralityJMS 113 JMS 0.530 JMS 0.571 JMS 0.489AU 57 AU 0.203 AU 0.466 AU 0.196
Table 1: Top centrality nodes of AN and WN according to four metrics. In all measuresAlvaro Uribe (AU) is the most central node of AN and the second most important ofthe WN. Former President Juan Manuel Santos (JMS) is the most important node by allmeasures of the WN. Other nodes are Germ´an Vargas Lleras (GV, Vice President underJuan Manuel Santos)) and Enrique Pe˜nalosa (EP, former Mayor of Bogota).
It is interesting to note that, on the one hand, there is a large proportionalgap between Alvaro Uribe’s score in Degree and Betweenness measurementsand the second most central nodes.Degree centrality (DC) is a simple yet effective way of measuring theimportance of a node and corresponds to the number of edges connected toit. Betweeness centrality (BC) assumes that information travels from nodeto node following the shortest path[16]. The BC of a node is defined as: BC ( i ) = (cid:88) i (cid:88) j ρ ( i, j, k ) ρ ( j, k ) , i (cid:54) = j (cid:54) = k (2)where ρ ( j, k ) is the number of shortest paths connecting nodes i and k and ρ ( j, i, k ) is the number of shortest paths connecting j and k passing through i . A rapid inspection of the network shows that Alvaro Uribe has manyalliances with low-degree nodes, as showin in Figure 4. Since DC measuresthe number of edges connected to a node (independently of the importance ofthe nodes it attaches with) and BC measures the number of shortest pathspassing through a given node (again, independently of the importance ofthe paths), it is logical that having many connections, even to unimportantnodes, will boost these scores. 8 igure 4: DC histogram for the immediate neighbors of the Alvaro Uribe node in theAN. Most of the nodes connected to Alvaro Uribe have a very low degree. On the other hand, Alvaro Uribe’s Eigencentrality score (EC) is onlymarginally larger than other nodes. This measure is based on the conceptthat being connected to high-scoring nodes will contribute more to the cen-trality than being connected to low-scoring nodes, resulting in a more dis-tributed centrality. The EC of a vertex v i in a graph G is defined as: EC ( v i ) = 1 λ (cid:88) j ∈ G a i,j EC ( v j ) (3)where a i,j is the value in row i and column j of A , the adjacency matrix of G . One may rewrite Equation 3 as the eigenvector definition: A x = λ x . (4)Variations of EC in which a node’s centrality is determined by the cen-trality of its neighbors and being connected to high-ranking nodes increasesthe influence in the network, are used to determine the ranking of webpages, e.g. Google’s Pagerank algorithm [38] or the citation impact of academic ar-ticles [51, 6]. In the political context, it provides a strong incentive for actorswith a limited political power to establish alliances with central nodes suchas Uribe, thus increasing the latter’s influence in a self perpetuating processconsistent with the preferential attachment mechanism.9 igure 5: DC histogram for the immediate neighbors of the Juan Manuel Santos nodein the WN. The highest connected node corresponds to Alvaro Uribe under whom JuanManuel Santos served as a Minister of Defense.
The WN is dominated by the figure of Juan Manuel Santos, who, as wepreviously explained, rose to the Presidency with the support of his formerally Uribe. Alvaro Uribe criticized Juan Manuel Santos’s peace talk efforts,announced shortly after being sworn in, and has become one of his fiercestcritics.Besides Juan Manuel Santos and Alvaro Uribe, the top positions of theWork network are dominated either by former Presidents or by high-rankingministers who have served under different Presidents. This, together with thedifference in size of the AN and WN network (Figure 2), tends to confirmthe diagnostics of how, despite the changes stated in the 1991 constitution,Colombia remains a highly centralized nation with a large state-bureaucracyorbiting, mainly, around the executive branch of the government.The higher centrality of Juan Manuel Santos over Alvaro Uribe in the WNis also consistent with their public discourses. Whereas Juan Manuel Santosinsisted on the need to work towards peace construction and, consequently,created bureaucratic positions to negotiate and implement peace accords,Alvaro Uribe’s discourse and public figure are centered on efficiency, actionover reflection and the reduction of the size of the government, all points10 igure 6: AN graphical representation. Size is proportional to the node degree and colorscorrespond to communities detected by the first cut of a Girvan-Newman algorithm. Aclear fracture between the close supporters of Alvaro Uribe and the rest of the politicalscene may seen. which align with the description of neo-populism given by Fierro [20].It is interesting to note that one of the main criticisms of Alvaro Uribeand his party allies against Juan Manuel Santos is the alleged wide-spreaduse of pork barrel politics, i.e. the appropriation of government spendingfor political gain. The use of key word repetition tactics by the CD onthis point has made the Spanish word for “sweet jam” ( “mermelada” ) afunctional synonym of pork barrel in Colombia and popularized the use ofthe expression “spread the sweet jam” ( “repartir mermelada” ) to describethis practice [3].
The complete AN and WN are displayed in Figures 6 and 8, respectively.The position of the nodes is calculated using a “force based” layout algorithm[30] which iteratively attracts linked nodes and repels non-attached nodes.11 .3.1. AN Community Analysis
The most notable characteristic of the AN is how the node correspondingto Alvaro Uribe, despite having the high centrality values shown in Table 1,distances itself from most other nodes with which it does not share edges.The polarizing tendency is confirmed via community analysis using theGirvan-Newman (GN) algorithm [24]. GN calculates the number of shortestpaths between all nodes passing through each edge and removes the edgewith the highest count. When an edge removal makes the graph discon-nected the resulting connected components are considered communities andthe process repeats for each component. In AN we consider only the graph’sfirst partition.The first cut of AN results in two communities containing 69 .
27% and30 .
73% of the nodes. The smaller community (shown in Figure 6) centersaround Alvaro Uribe and contains many members of his party’s inneokr circleincluding Colombia’s current president Ivan Duque.The algebraic connectivity, also known as the the Fiedler eigenvalue [19,9], of a graph G may be used to partition the graph partition. The Fiedlervector is the eigenvector corresponding to the second smallest eigenvalue ofthe Laplacian matrix L of G where L = D − A, (5) A corresponds to the adjacency matrix of G and D to the degree matrix of A : D i,j := (cid:26) deg ( v i ) if i = j G . For the AN this results in a similar separationwith only 5 nodes migrating from the largest to the smallest community. Theproportional number of nodes remain similar resulting in 64 .
58% and 35 . igure 7: There are three maximum cliques consisting of 5 nodes in the AN. All nodescorrespond to members of the CD who are or have been members of the congress includingformer president Alvaro Uribe (AU) and current president Ivan Duque (ID). Unlike the AN, the WN does not present any easily detectable communi-ties. The network revolves around Juan Manuel Santos and Alvaro Uribe, aspredicted by the centrality values, but there is a dense network of shared ver-tices (people who have had work relationships with both) which bind theminto one large community.The first three cuts of GN correspond to very small marginal communities(1 . .
51% and 1 .
13% of all the nodes) connected by single edges to themain component. It then separates a sizeable community ( 8 .
68% of thenodes) seen in the right side of Figure 8. This community is formed mostlyby politicians and technocrats who worked with Gustavo Petro, a prominentleft-wing opposition leader, during his tenure as Bogota Mayor (2012-2015).The WN has 5 maximum cliques containing 6 nodes each. The cliquesform two distinct communities bridged by Juan Manuel Santos who is a mem-ber of 4 of them (see Figure 9). The communities correspond to two distincttime periods: the negotiating team for the Havana Peace Accords (2012-2016) and members of former President Cesar Gaviria’s cabinet (1990-1994).Unlike the maximal cliques of the AN, the WN is formed by representativesof various parties and sectors.Whereas AN is formed by two easily separable communities, WN forms13 igure 8: WN graphical representation. Node colors correspond to the first five commu-nities detected by the Girvan-Newman algorithm. a tightly knit network without any strong separations. This would lead tothink that, unlike the political arena, in a a state as large and centralizedas Colombia it is necessary through time to draw people from all politicaltendencies to keep the machinery moving.
4. Conclusions
A network-based approach to populism is necessary because it brings nu-ance to both the overly structural analysis and to the pairing of influentialleader/faithful followers that so often is the backbone of the studies in pop-ulism. The massive popular support of a populist leader becomes the socialforce that allows eroding democratic institutions and mechanisms under hiswill, which is the most notorious danger of populism. That explains the in-terest in understanding both the leader’s followers, and the leader’s means14 igure 9: There are 5 maximum cliques consisting of 6 nodes in the WN. Two communitiesbridged by former President Juan Manuel Santos (JMS) may be seen: A community formedby members of the Havana Peace Accords negotiating teams (left) and a clique formed bymembers of the cabinet of former President Cesar Gaviria (CG, right). to obtain support, by analyzing voting dispositions, discourse, ideology, andeven personality traits in both voters and the leader. Additionally, studiesof populist regimes also seek for explanations in structural terms: what arethe social and economic conditions that allow a populist movement to thrive.These are all fundamental questions. However, they oscillate between a mi-cro and a macro level. The network approach allows us to address the mesolevel by rendering visible the paths that connect the leader and the voters.These paths are made of politicians, advisors, and high-rank State officialsthat cement and increase or erode and diminish a populist leader’s power.A characteristic of populist leaders is their presentation as outsiders.Uribe, launching his presidential campaign as an independent candidate, wasnot an exception. But just because someone presents him or herself as a po-litical outsider does not mean that it is not playing the political game offorging alliances. Mapping the political landscape of Colombia allowed us tosee the extent of Uribe’s partnerships and the uniqueness of his connections incomparison to other former Presidents. They are not nearly as interlinked ashim and correspondingly their political presence is more marginal. Populistleaders need not only charisma, discourse, or ideology to get and maintainpolitical power but some good old networking.
5. Future research
The data provided by the news website takes into account the most no-table figures in Colombian politics based on their significance in a given news15ycle, which makes it necessary to explain to the readers who the person is.Therefore, it is essential to build a database that includes not only the no-table figures but also the ones that are less visible and equally powerful. Thisdatabase would require collecting information about all the members bothfrom the Congress and from the top Government positions. Additionally, thenetwork approach to populism would benefit from tracing the changes in thealliances throughout the emergence and decline of a populist regime. Ourlong-term goal is to use the network morphology to create a populism indica-tor by strengthening the database and incorporating a historical perspectivein the analysis.
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