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Consequences OF Speaking OUT Against Radical Right
Research Design and Method Selection (SPS4003)
University of Glasgow
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THE UNINTENDED CONSEQUENCES OF SPEAKING OUT AGAINST RADICAL RIGHT Citizens with liberal stances often voice their concerns as radical right represents the erosion of democracy publicly oppose the radical right in order to discredit it, to signals its untrustworthiness as well as it contribution to democratic erosion WHICH ARE THE CONSEQUNCES OF EXPOSING THE RADICAL RIGHT? Research question: How effective is speaking out publicly against the radical right? Does it hollow its influence or, instead, does it help to consolidate the influence of the radical right? How to reply to those questions? Looking at Twitter interactions for 3 reason: to measure how citizens interact with radical right parties and supporters on a daily basis , Twitter is an asymmetrical social media allowing to read and share anybody, meaning a higher level sof exposure to heterogenous political stances, contents tend to be highly polarized and emotionally charged opposing the radical right tends to feed it for mainly 2 reasons: engaging with it, citizens help to spread its message on the platform reaching users who would otherwise not have contact with such contents radical rights thrives on being perceived as against the liberal establishment , enjoying to be trashed the What does it mean for them to be influential on Twitter? Influence on number of followers as sign of credibility, trustworthiness, and wider spectrum of reaches comparing the data on Twitter, it is possible to see who contributes the most to the increase in the numbers of followers of the radical right Case study: Portugal and the Chega party founded in 2019 André Ventura who in 2021 gather 11 of the votes in the presidential elections using a data set over 1 MLN tweets and a windows of observation from 2017 through 2021 Methodology used: Node embedding (allows to encode Twitter interactions into mathematical space and analyse not only the distance between the users but also their allows us to map twitter interactions as an input to downstream classification tasks in machine learning settings) both allows to visualize and analyse similar functioning to word embedding but the node encoded graphs users whose network behaviour is similar are encoded closely in the embedding space encouraging ideological proximity Automated sentiment detection method to measure the negative and positive sentiments that users relay in their quoted tweets , usually for the sentiment classification in political science we relied on approaches but due to the shortness of the tweets and slang used effective so we rely on approach using transfer learning as the process of transferring knowledge between different learning tasks Vector to measure the evolution in the number of followers of Chega over a given period of time 4 different sentiments categories: positive, negative, neutral anc inconclusive five variables to be autoregressive and endogenous meaning mutually influence each other Data: selecting influential twitter accounts in the Portuguese context (327), only quoted tweets which contain text Results Obtained: the growing influence of the radical right on twitter benefits the most from users who publicly oppose it help to spread their message even wider , while who publicly support the radical right have only a very limited contribution to its increasing success During the observation window Chega posted 834 tweets , increasing of followea from 131 to increasing also in the party members , more negative quotes than positive meaning an higher exposure , higher point was around 2020 coincing with the leader unsuccessful legislative proposal to approve confinement measure targeted at the Roma minority Evidence suggests that the higher the cosine distance between users and Chega in the graph, the higher the negative sentiment their quoted tweets evince. Only users with a small cosine distance to Chega tend to quote the tweets and whole expressing positive sentiments The number of tweets have little impact on the growth of followers Limitations of the study: casual nature of the findings (?) what do you mean that? Cautions bout the extent to which the findings are representative beyond twitter Background info: authoritarian regime, validation and normalization of the most illiberal citizens point of view the liberal democracy is no longer the only game in town Why citizens react? Perceived as a threat to liberal social identity theory meaning the establishment of boundaries between social group based on values and preferences remember that citizens who publicly oppose the radical right do not necessarily share preferences , likely to have an heterogeneous political preferences Immigration as issue Electoral system and party financing model creates obstacle for party change Strong stigmatization of centre right because of Salazar regime Chega (Roma minority and elite) HOW? Social media as a and highly effective environment to amplify the right populist discourse it promotes the opportunity to interact with acquaintances, or friends of friends via the weak ties (connecting the centre with the periphery, the bigger the network, the higher the likelihood that users will interact with asymmetrical and unidirectional fashions, fewer constraints in interaction) Also they interact because Twitter users have incentives to react to foes, particularly in affective polarization contexts with (perceived) increasing threats to liberal values. Consequences: the Cascade effect of retweeting a quotes, helping increase the visibility of illiberal stances , reinforced the stances of the radical the higher the number of quoted tweets with negative sentiment, the higher the increase in the number of radical right followers on Twitter
Consequences OF Speaking OUT Against Radical Right
Module: Research Design and Method Selection (SPS4003)
University: University of Glasgow
