PL EU: emoji, language games and political polarisation

Are emoji political? In an increasing body of research, emoji have variably been viewed as emotional data or personality identifiers. However, little attention has been paid to the social and political import of emoji. Using a dataset of politically active Twitter users in Poland, including 334 members of parliament and their 1,288,950 followers, we ask whether emoji are used for political self-representation, and discuss the implications for political identity formation and mobilisation online. Adapting a new method of ideal point estimation, we identify patterns in the employment of emoji in user Twitter bios across a latent political space computed from a Twitter following network. We find that emoji are used as stand-ins for o昀ffiine political symbols such as, and . Additionally, we find that the use of emoji without recognisable political meaning, such as,, and is contingent on a users estimated political ideal point. Users on the left are likelier to employ and, while those on the right are likelier to employ and . Using Ludwig Wittgenstein’s theory of language games, we argue that this points to the use of emoji for communication of both political values and affect, and to the development of a new political language game of emoji

Your most telling friends: Propagating latent ideological features on Twitter using neighborhood coherence

Multidimensional scaling in networks allows for the discovery of latent information about their structure by embedding nodes in some feature space. Ideological scaling for users in social networks such as Twitter is an example, but similar settings can include diverse applications in other networks and even media platforms or e-commerce. A growing literature of ideology scaling methods in social networks restricts the scaling procedure to nodes that provide interpretability of the feature space: on Twitter, it is common to consider the sub-network of parliamentarians and their followers. This allows to interpret inferred latent features as indices for ideology-related concepts inspecting the position of members of parliament. While effective in inferring meaningful features, this is generally restrained to these sub-networks, limiting interesting applications such as country-wide measurement of polarization and its evolution. We propose two methods to propagate ideological features beyond these sub-networks: one based on homophily (linked users have similar ideology), and the other on structural similarity (nodes with similar neighborhoods have similar ideologies). In our methods, we leverage the concept of neighborhood ideological coherence as a parameter for propagation. Using Twitter data, we produce an ideological scaling for 370K users, and analyze the two families of propagation methods on a population of 6.5M users. We find that, when coherence is considered, the ideology of a user is better estimated from those with similar neighborhoods, than from their immediate neighbors.Comment: 8 pages, 2020 ASONAM Conferenc

Multidimensional political polarization in online social networks

Political polarization in online social platforms is a rapidly growing phenomenon worldwide. Despite their relevance to modern-day politics, the structure and dynamics of polarized states in digital spaces are still poorly understood. We analyze the community structure of a two-layer, interconnected network of French Twitter users, where one layer contains members of Parliament and the other one regular users. We obtain an optimal representation of the network in a four-dimensional political opinion space by combining network embedding methods and political survey data. We find structurally cohesive groups sharing common political attitudes and relate them to the political party landscape in France. The distribution of opinions of professional politicians is narrower than that of regular users, indicating the presence of more extreme attitudes in the general population. We find that politically extreme communities interact less with other groups as compared to more centrist groups. We apply an empirically tested social influence model to the two-layer network to pinpoint interaction mechanisms that can describe the political polarization seen in data, particularly for centrist groups. Our results shed light on the social behaviors that drive digital platforms towards polarization, and uncover an informative multidimensional space to assess political attitudes online

Aspects théoriques et numériques des phénomènes de propagation d’ondes dans domaines de géométrie complexe et applications à la télédétection

This thesis is about some boundary integral operators defined on the unit disk in a three-dimensional spaces, their relation with the exterior Laplace and Helmholtz problems, and their application to the preconditioning of the systems arising when solving these problems using the boundary element method.We begin by describing the so-called integral method for the solution of the exterior Laplace and Helmholtz problems defined on the exterior of objects with Lipschitz-regular boundaries, or on the exterior of open two-dimensional surfaces in a three-dimensional space. We describe the integral formulation for the Laplace and Helmholtz problem in these cases, their numerical implementation using the boundary element method, and we discuss its advantages and challenges: its computational complexity (both algorithmic and memory complexity) and the inherent ill-conditioning of the associated linear systems.In the second part we show an optimal preconditioning technique (independent of the chosen discretization) based on operator preconditioning. We show that this technique is easily applicable in the case of problems defined on the exterior of objects with Lipschitz-regular boundary surfaces, but that its application fails for problems defined on the exterior of open surfaces in three-dimensional spaces. We show that the boundary integral operators associated with the resolution of the Dirichlet and Neumann problems defined on the exterior of open surfaces have inverse operators, and that these operators would provide optimal preconditioners, but that they are not easily obtainable. Then we show a technique to explicitly obtain such inverse operators for the particular case when the open surface is the unit disk in a three-dimensional space. Their explicit inverse operators will be given, however, in the form of series, and will not be immediately applicable in the use of boundary element methods.In the third part we show how some modifications to these inverse operators allow us to obtain variational explicit and closed form expressions, no longer expressed as series, but also conserve nonetheless some characteristics that are relevant for their preconditioning effect. These explicit and closed forms expressions are applicable in boundary element methods. We obtain precise variational expressions for them and propose numerical schemes to compute the integrals needed for their use with boundary elements. The proposed numerical methods are tested using identities available within the developed theory and then used to build preconditioning matrices. Their performance as preconditioners for linear systems is tested for the case of the Laplace and Helmholtz problems for the unit disk. Finally, we propose an extension of this method that allows for the treatment of cases of open surfaces other that the disk. We exemplify and study this extension in its use on a square-shaped and an L-shaped surface screen in a three-dimensional space.Cette thèse s'inscrit dans le sujet des opérateurs intégraux de frontière définis sur le disque unitaire en trois dimensions, leurs relations avec les problèmes externes de Laplace et Helmholtz, et leurs applications au préconditionnement des systèmes linéaires obtenus en utilisant la méthode des éléments finis de frontière.On décrit d'abord les méthodes intégrales pour résoudre les problèmes de Laplace et de Helmholtz en dehors des objets à frontière régulière lipschitzienne, et en dehors des surfaces bidimensionnelles ouvertes dans un espace tridimensionnel. La formulation intégrale des problèmes de Laplace et de Helmholtz pour ces cas est décrite formellement. La mise en oeuvre d'une méthode numérique utilisant la méthode des éléments finis de frontière est également décrite. Les avantages et les défis inhérents à la méthode sont abordés : la complexité du calcul numérique (de mémoire et algorithmique) et le mal conditionnement inhérentes à des systèmes linéaires associés.Dans une deuxième partie on expose une technique optimale de préconditionnement (indépendante de la discrétisation) sur la base des opérateurs intégraux de frontière. On montre comment cette technique est facilement réalisable dans le cas de problèmes définis en dehors d'un objet régulier à frontière lipschitzienne, mais qu'elle pose des problèmes quand ils sont définis en dehors d'une surface ouverte dans un espace tridimensionnel. On montre que les opérateurs intégraux de frontière associés à la résolution des problèmes de Dirichlet et Neumann définis en dehors des surfaces ont des inverses bien définis. On montre également que ceux-ci pourraient conduire à des techniques de préconditionnement optimales, mais que ses formes explicites ne sont pas faciles à obtenir. Ensuite, on montre une méthode pour obtenir de tels opérateurs inverses de façon explicite lorsque la surface sur laquelle ils sont définis est un disque unitaire dans un espace tridimensionnel. Ces opérateurs inverses explicites seront, cependant, en forme des séries, et n'auront pas une adaptation immédiate pour leur utilisation dans des méthodes des éléments finis de frontière.Dans une troisième partie on montre comment certaines modifications aux opérateurs inverses mentionnés permettent d'obtenir des expressions variationnelles explicites et fermées, non plus sous la forme des séries, en conservant certaines caractéristiques importantes pour l'effet de préconditionnement cherché. Ces formes explicites sont en effet applicables aux méthodes des éléments finis frontière. On obtient des expressions variationnelles précises et on propose des calculs numériques pour leur utilisation avec des éléments finis frontière. Ces méthodes numériques sont testées en utilisant différentes identités obtenues dans la théorie développée, et sont ensuite utilisées pour produire des matrices préconditionnantes. Leur performance en tant que préconditionneurs de systèmes linéaires associés à des problèmes de Laplace et Helmholtz à l'extérieur du disque est testée. Enfin, on propose extension de cette méthode pour couvrir les cas de surfaces diverses. Ceci est illustré et étudié dans les cas précis des problèmes extérieurs à des surfaces en forme de carré et en forme de L dans un espace tridimensionnel

Discovering ideological structures in representation learning spaces in recommender systems on social media data

Recommender systems in social platforms attract attention in part because of their potential impact over political phenomena, such as polarization or fragmentation of online communities. These research topics are also important because of the need for understanding systemic effects in view of upcoming risk-oriented AI regulation in the EU and the US. A common approach leverages outcomes of recommendations to audit recommender systems. A different approach is that of explainability, seeking to render recommendation mechanisms intelligible to humans, potentially enabling both auditing and actionable design tools. This second approach is particularly challenging in the context of online systems of political opinions because of the intrinsic unobservability of opinions. In this article we leverage multi-dimensional political opinion estimation of large online populations (along a left-right dimension but also along other political dimensions) to investigate latent spaces in representation learning computed by recommender systems. We train a recommender based on ubiquitous collaborative filtering principles using data on content sharing on Twitter by a large population, evaluating accuracy and extracting a latent space representation leveraged by the recommender. On the other hand, we leverage multi-dimensional political opinion inference to position users in political spaces representing their opinions. We then show for the first time the relation between latent representations leveraged by a recommender system and the spatial representation of users. We show that some dimensions learned by the recommender capture ideological positions of users, bridging politics and algorithmics in our social and al-gorithmic system, opening a path towards political explainability of AI

About Some Boundary Integral Operators on the Unit Disk Related to the Laplace Equation

International audienceWe introduce four integral operators related to the Laplace equation in three dimensions on the circular unit disk. Two of them are related to the weakly singular operator and the other two are related to the hypersingular operator. We provide series expressions for their kernels using proposed bases for the Sobolev trace spaces involved in the symmetric Dirichlet and antisymmetric Neumann Laplace screen problems on the disk. We then provide explicit and closed variational forms suitable for boundary element computations. We develop numerical computation schemes for the associated Galerkin matrices and test their use as preconditioners for the matrices arising from the integral equations associated with the solution of the mentioned screen problems

Tweeting Apart: Democratic Backsliding, New Party Cleavage and Changing Media Ownership in Turkey

International audienceTurkey plunges headlong into democratic backsliding under Erdoğan's presidency. The country was a forerunner in the decline of democratic standards in a decade from 2010 to 2020. In the first part of the article, we investigate how this democratic erosion suspends Turkey's long-standing traditional party cleavage between religious conservatism and secularism. By tracing individuals who follow the members of the Turkish parliament on Twitter, we attach the deputies to their followers with the help of political embedding of Twitter networks. We illustrate that, as the ethnic identity divide remains significant, democracy-authoritarianism cleavage becomes the main party split that brings the supporters of an ideologically diverse group of opposition parties closer. In the second part, we conceptualize the democracy-authoritarianism divide as the main cleavage in Turkish party politics after 2017 to shed light on how the AKP's different tactics of capturing traditional media generated a partisan media landscape

Modeling both pairwise interactions and group effects in polarization on interaction networks

International audienceThe study of polarization has gained increasing attraction in the past decades. Since observing both opinions and interactions is challenging, epistemic programs such as agent-based models have been proposed as a means to assessing the systemic consequences of social psychology mechanisms. Most results in agent-based models for opinion dynamics have focused on individual opinion constructs and pairwise interactions, with a few works treating group effects as constraints. Meanwhile, a tradition in social sciences has been putting emphasis on how group configuration affects individual behavior. In this work, we introduce a new model for accounting for both pairwise interactions in which actors observe and update opinions, and individual perception of the evolving configuration of groups that make up the population in which they are embedded. Through experiments, we show that different treatment given to pairwise interactions, depending on whether they occur between in-groups or out-groups, has quantifiable impacts in the resulting polarization of a population. In particular, the tolerance toward out-group opinions is shown to have a strong impact on the resulting polarization. Our model produces and accounts for polarized states resulting from group consolidation and fragmentation

Modeling both pairwise interactions and group effects in polarization on interaction networks

International audienceThe study of polarization has gained increasing attraction in the past decades. Since observing both opinions and interactions is challenging, epistemic programs such as agent-based models have been proposed as a means to assessing the systemic consequences of social psychology mechanisms. Most results in agent-based models for opinion dynamics have focused on individual opinion constructs and pairwise interactions, with a few works treating group effects as constraints. Meanwhile, a tradition in social sciences has been putting emphasis on how group configuration affects individual behavior. In this work, we introduce a new model for accounting for both pairwise interactions in which actors observe and update opinions, and individual perception of the evolving configuration of groups that make up the population in which they are embedded. Through experiments, we show that different treatment given to pairwise interactions, depending on whether they occur between in-groups or out-groups, has quantifiable impacts in the resulting polarization of a population. In particular, the tolerance toward out-group opinions is shown to have a strong impact on the resulting polarization. Our model produces and accounts for polarized states resulting from group consolidation and fragmentation