Critical discourse analysis investigates the ways in which discourse is to abuse power relationships. Political debates constitute discourses that mirror certain aspects of ideologies. This study aimed to uncover the ideological intentions in the formulation and circulation of hegemonic political ideology in TV political debates that occurred in the 2011-2012 Yemen revolution, examining the question of how ideology was used as a tool of hegemony. The corpus of the study consisted of fifteen debates (73915 words) from four live debate programmes (The Opposite Direction, In Depth, Behind the News and the Revolution Talk) staged at Al Jazeera Arabic TV channel between 2011 and 2012. Al Jazeera was selected as the focus of this study because of its position as the most popular TV in the Arab world and due to its strong presence during the Arab revolutions. Two debate sides were identified: government, representing the president Ali Abdullah Saleh and his regime, and protesters, who represented the discontent populace gathering squares who demanded the abdication of the president. Data were also obtained from interviews conducted with the Al Jazeera staff who managed the debates. Analysis was conducted on the verbal discourse aspects of four debates, one debate from each programme, using critical discourse analysis: aspects from the van Leeuwen's (2008, 2009) Social Actor Network model, supplemented by additional linguistic features. The results were triangulated using computer-assisted corpus analysis for the entire corpus, the fifteen debates. AntConc (version 3.2.4w) was used to process the keyword lists, word concordances and collocations. The results of the analysis were then compared with the interviews with AJ staff. The main research finding was that although results of the critical discourse analysis correlated with those of the computer-assisted corpus analysis, they differed to a marked degree from the perceptions of Al Jazeera staff. Also, evident is that Al Jazeera and the protesters had similar ideological intentions, including glorifying the revolution and inciting protests, which was not the case with the government speakers. Overall, the findings show that Al Jazeera displayed evident bias, excluding the government from its debates in a way that runs counter to its mission statement and the tenets of objective journalism. The findings of this study illustrate the powerful role that language plays in shaping ideological media intentions and influencing the media audience.

[ES] En esta tesis abordamos el problema de la detección de las opiniones (stance detection, SD) en las redes sociales, centrándose en los debates políticos polarizados en Twitter. La SD consiste en determinar automáticamente si el autor de una publicación está a favor o en contra de un objetivo de interés, o si no se puede inferir la opinión. Nos ocupamos de temas políticos como las elecciones políticas y los referendos y, como resultado, los objetivos son tanto personas como referendos. También exploramos las comunicaciones que tienen lugar en estos debates polarizados, arrojando luz sobre las dinámicas de comunicación entre personas que tienen opiniones en acuerdo o en conflicto, enfocándonos en particular en la observación del cambio de opiniones (opinion shifting). Proponemos modelos de aprendizaje automático para la SD como si fuera un problema de clasificación binaria. Exploramos características basadas en el contenido del texto del tweet, además usamos características basadas en información contextual que no emerge directamente del texto. Utilizando el corpus de benchmark propuesto para la tarea compartida sobre la SD realizado para SemEval 2016, exploramos la contribución que el estudio de las relaciones entre el objetivo de interés y las otras entidades involucradas en el debate proporciona a la SD. Al participar en la tarea ``Stance and Gender Detection in Tweets on Catalan Independence'' organizado para IberEval 2017, hemos propuesto otras características textuales y contextuales para la SD en tweets en español y en catalán. Explorando la SD desde una perspectiva multilingüe, hemos creado un corpus de tweets en francés y uno en italiano. La extensión multilingüe de nuestro modelo (multiTACOS) muestra que la SD está influenciada más por los diferentes estilos utilizados por los usuarios para comunicar la opinión sobre objetivos de diferentes tipos (personas o referendos) en lugar del idioma utilizado. Con el objetivo de recuperar información contextual sobre la red social de los usuarios de Twitter (generalmente las tareas compartidas solo consisten en el contenido del tweet, dejando de lado la información sobre el usuario), hemos creado otros dos conjuntos de datos, uno en inglés y uno en italiano, respectivamente, sobre el Brexit (TW-BREXIT) y sobre el referéndum constitucional italiano (ConRef-STANCE-ita). En ambos casos de estudio, mostramos que los usuarios tienden a agruparse en grupos con ideas similares. Por este motivo, el modelo que explota el conocimiento de la comunidad social a la que el autor del tweet pertenece, supera los resultados obtenidos utilizando solo las funciones basadas en el contenido de la publicación. Además, la evidencia muestra que los usuarios utilizan diferentes tipos de comunicación según el nivel de acuerdo con la opinión del interlocutor, por ejemplo, las relaciones de amistad, los retweets y las citas (quote) son más comunes entre los usuarios relacionados, mientras que las respuestas (replies) se utilizan a menudo para interactuar con usuarios que tienen diferentes posiciones. Al abordar la SD desde una perspectiva diacrónica, también observamos tanto el cambio de opinión como la mitigación del debate hacia posiciones neutrales después del resultado de la votación. Además, hemos observado que tener contacto con una variedad más amplia de opiniones puede influir en la propensión a cambiar de opinión. Finalmente, mostramos que las características basadas en una representación gráfica de un dominio de interés no se limitan a la SD, sino que se puede aplicar a diferentes escenarios. Al proponer otra tarea de clasificación que realiza la identificación del talento en el deporte, especialmente en el estudio de caso del tenis de mesa, mostramos que las métricas de redes basadas en la centralidad son una señal fuerte para el talento y pueden usarse para entrenar un modelo de algoritmo de aprendizaje automático para enfrentar esta / [CAT] En aquesta tesi doctoral abordem el problema de la detecció de posició (stance detection, SD) en els mitjans de comunicació social, especialment centrat en els debats polítics polaritzats a Twitter. La SD consisteix a determinar automàticament si l'autor d'una publicació està a favor o en contra d'un objectiu o tema d'interès, o si l'opinió envers d'aquest objectiu o tema determinat no es pot inferir. Ens ocupem de temes polítics com ara esdeveniments electorals i, en conseqüència, els temes d'interès són, en concret, la SD en vers dirigents polítics i referèndums. També explorem les comunicacions que es duen a terme en aquests debats polaritzats, que posen de manifest la dinàmica de les comunicacions entre les persones que tenen opinions concordants o contrastades, especialment centrant-nos en l'observació del canvi de les opinions. Proposem models d'aprenentatge automàtic per abordar la SD com un problema de classificació. Explorem les funcions basades en el contingut textual del tweet, però també les funcions basades en la informació contextual que no afloren directament del text. Utilitzem el conjunt de dades de referència en anglès proposat per a les tasques compartides sobre SD celebrades a SemEval 2016, per explorar la contribució a la SD d'investigar les relacions entre l'objectiu d'interès i les altres entitats implicades en el debat. En la participació a la tasca compartida de ``Stance and Gender Detection in Tweets on Catalan Independence'' celebrada a IberEval 2017, es van proposar altres trets textuals i contextuals per detectar la posició dels autors dels tweets, escrits en espanyol i en català, envers la independència de Catalunya. L'extensió multilingüe del model de SD (multiTACOS) mostra que la SD es veu afectada pels diferents estils que utilitzen els usuaris per comunicar la posició envers objectius de diferents tipus (persones o referèndum) més que la llengua utilitzada. Amb l'objectiu de recuperar informació contextual sobre la xarxa social dels usuaris de Twitter (les tasques compartides solen publicar només el contingut del tweet i deixen de banda, en canvi, la informació sobre la persona que escriu el tweet), vam crear dos conjunts més de dades, un en anglès i un en italià, el corpus Brexit (TW-BREXIT) i el corpus del referèndum constitucional italià (ConRef-STANCE-ita) respectivament. En els dos casos, demostrem que els usuaris tendeixen a agrupar-se en grups d'opinió o creences similars. Per aquest motiu, el model aprofita el coneixement de la comunitat social en línia al qual pertany el tweeter i supera els resultats obtinguts utilitzant només funcions basades en el contingut de la publicació. És més, els experiments també mostren que els usuaris fan servir diferents tipus de comunicació en funció del nivell d'acord amb l'opinió del seu interlocutor, és a dir, les relacions d'amistat (friendship), retweets i cotitzacions (quotes) són més freqüents entre els usuaris amb idees afins, mentre que les respostes (replies) s'utilitzen sovint per interactuar amb els usuaris que tenen posicions o opinions diferents. A l'hora d'abordar la SD des d'una perspectiva diacrònica, també observem el canvi d'opinió i la mitigació del debat cap a una posició no alineament després del resultat de la votació. A continuació, observem que l'accés a una major diversitat de punts de vista pot influir en la propensió a canviar l'opinió personal. Finalment, mostrem que la utilitat de les funcions basades en una representació gràfica d'un domini d'interès no es limita a la SD, sinó que es pot aplicar a diferents escenaris. Proposar una altra tasca de classificació que realitzi la identificació de talent en l'esport, especialment centrada en l'estudi de cas del tennis de taula, mostrem que les xarxes mètriques basades en la centralitat són un fort senyal per a detectar el talent i també es pot utilitzar per a l'entrenament d'un model d'algorisme d'ap / [EN] In this thesis, we address the problem of stance detection (SD) in social media focusing on polarized political debates in Twitter. SD consists in automatically determine whether the author of a post is in favor or against a target of interest, or whether the opinion toward the given target can not be inferred. We deal with political topics such as electoral events and consequently the targets of interest are both politicians and referendums. We also explore the communications which take place in these polarized debates shedding some light on dynamics of communications among people having concordant or contrasting opinions, particularly focusing on observing opinions' shifting. We propose machine learning models for addressing SD as a classification problem. We explore features based on the textual content of the tweet, but also features based on contextual information that do no emerge directly from the text. Using the English benchmark dataset proposed for the shared tasks on SD held at SemEval 2016, we explore the contribution on SD of investigating the relations among the target of interest and the other entities involved in the debate. Participating to the ``Stance and Gender Detection in Tweets on Catalan Independence'' shared task held at IberEval 2017, we proposed other textual and contextual based features for detecting stance on Spanish and Catalan tweets. With the main aim of facing SD in a multilingual perspective and having an homogeneous setting for multi-language comparisons, we collected tweets in French and Italian also. The multilingual extension of our SD model (multiTACOS) shows that SD is affected by the different styles used by users for communicating stance towards target of different types (persons or referendum) more than the used language. With the aim of retrieving contextual information about the social network of Twitter's users, we created other two datasets, one in English and one in Italian, respectively about the Brexit (TW-BREXIT) and the Italian Constitutional referendum (ConRef-STANCE-ita). In both the case studies, we show that users tend to aggregate themselves in like-minded groups. For this reason, the model takes advantage of knowing the online social community the tweeter belongs to and outperforms the results obtained by using only features based on the content of the post. Furthermore, experiments show that users use different type of communication depending on the level of agreement with the interlocutor's opinion, i.e., friendship, retweets, and quote relations are more common among like-minded users, while replies are often used for interacting with users having different stances. Addressing SD in a diachronic perspective, we also observe both opinion shifting and a mitigation of the debate towards an unaligned position after the outcome of the vote. Then, we observe that accessing to a larger diversity of point of views can influence the propensity to change the personal opinion. We finally show that the usefulness of features based on a graph representation of a domain of interest is not limited to SD, but can be applied to different scenarios. Proposing another classification task that performs talent identification in sport, particularly focusing on the case study of table tennis, we show that networks metrics based on centrality are strong signal for talent and can be used for training a machine learning algorithm model for this task too. / Lai, M. (2019). On Language and Structure in Polarized Communities [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/119116 / TESIS

This study compares the frequency and types of hedging devices used in the presidential debate of 2020 between Donald Trump and Joe Biden. Many studies have investigated hedging in political discourse, which has been shown to function as a rhetorical strategy in contexts such as political press interviews and political debates. The current study applied corpus linguistic methodology by creating a corpus of transcripts of the two presidential debates of 2020. To establish what types of hedges were used, a theoretical framework from Fraser (2010a) was used to classify the hedges into two main categories: Propositional hedges and Illocutionary hedges. A manual search showed that hedges did occur in the presidential debate and were used by both candidates to some extent. Based on the results, it could be argued that the hedging appearing in the debates was mainly used to create vagueness, express caution, evade taking responsibility for the validity of a statement, and show a lack of commitment to an utterance. The results further showed that Trump used hedges more frequently than Biden did. However, the scope of this study is not suited to make any reliable assumptions regarding whether frequent use of hedging is negative or positive.

Transparency International published its annual corruption perceptions index in 2022, where Sweden obtained the highest measured level of perceived corruption in eleven years. At about the same time, an investigation into corruption and undue influence was discarded by the newly appointed government. The purpose of this thesis is to examine two current political debates about corruption through Norman Faircloughs model for critical discourse analysis. In more detail, the objectives are to study which discourses that can be distinguished, the characteristics of the discursive struggle and which discourse that dominates the Swedish corruption debate. In this thesis, political debates are considered as usable contexts to illustrate both contradiction and consensus regarding the corruption in Sweden. By using critical discourse analysis as an approach, the ambition is to visualize how politicians construct the image of the increased corruption and to examine how certain statements are presented as more evident or true than others. This study shows that there are four discourses that can be distinguished in the two political debates on corruption: privatization, increasing crime rate, accountability and openness and trust. The observed discursive struggle generally has high interdiscursivity, a few cases of intertextuality, and seems to be open to changes. The discourse that dominates the order of discourse is "the increasing crime rate". The results indicate that current societal problems, that are mainly highlighted by the ruling politicians, appear to have an impact on the political discussion about corruption in Sweden.

[pt] Com a emergência da internet e o constante aperfeiçoamento das Tecnologias da Informação e Comunicação (TICs) ao longo das últimas três décadas, verificase no Brasil, assim como no resto do mundo, a reconfiguração de forma virtualizada da esfera pública na qual as questões sociais são discutidas, observando-se, ainda, que interesses individuais, sociais, políticos e econômicos entrelaçam-se e apropriam-se uns dos outros na criação e manutenção de espaços para discussões, que, por sua vez, são amplamente utilizados como caixas de ressonância para que as mais variadas questões ecoem pela sociedade; é o caso da rede social conhecida mundialmente como Twitter. Assim, aliando-a às devidas complementações extraídas das obras de autores hodiernos como Eduardo Magrani e Evgeny Morozov, torna-se fundamental o recurso à teoria de Jürgen Habermas para que se possa entender a configuração, importância e problemas da atual esfera pública nacional, bem como para que se possa extrair conclusões sobre a racionalidade dos debates políticos travados dentro da plataforma Twitter, demonstrando que, sob o pretexto de fornecer um espaço de efetivação da práxis comunicacional cotidiana, a plataforma, na verdade, instrumentaliza interesses, e, consequentemente, promove a colonização do mundo da vida de seus usuários. Outrossim, em virtude do caráter pragmático-formal da teoria habermasiana, também se demonstra como um agente político influente pode se valer estrategicamente da plataforma para ascensão de seus interesses próprios através da análise de algumas de suas manifestações. / [en] The emergence of the internet and the constant improvement of Information and Communication Technologies (ICTs) over the last three decades, in Brazil, as in the rest of the world, the reconfiguration of the public sphere in which are discussed, also observing that individual, social, political and economic interests intertwine and appropriate each other in the creation and maintenance of spaces for discussions, which, in turn, are widely used as boxes of resonance so that the most varied issues echo through society; this is the case of the social network known worldwide as Twitter. Thus, combining it with the necessary complements extracted from the works of contemporary authors such as Eduardo Magrani and Evgeny Morozov, it is essential to resort to the theory of Jürgen Habermas in order to understand the configuration, importance and problems of the current national public sphere, as well as how to draw conclusions about the rationality of the political debates held within the Twitter platform, demonstrating that, under the pretext of providing a space for the realization of everyday communicational praxis, the platform actually instrumentalizes interests, and, consequently, promotes the colonization of the lifeworld of its users. Furthermore, due to the pragmatic-formal character of the Habermasian theory, it is also demonstrated how an influential political agent can strategically use the platform to advance its own interests through the analysis of some of its manifestations.