Fast filtering and animation of large dynamic networks

Detecting and visualizing what are the most relevant changes in an evolving network is an open challenge in several domains. We present a fast algorithm that filters subsets of the strongest nodes and edges representing an evolving weighted graph and visualize it by either creating a movie, or by streaming it to an interactive network visualization tool. The algorithm is an approximation of exponential sliding time-window that scales linearly with the number of interactions. We compare the algorithm against rectangular and exponential sliding time-window methods. Our network filtering algorithm: i) captures persistent trends in the structure of dynamic weighted networks, ii) smoothens transitions between the snapshots of dynamic network, and iii) uses limited memory and processor time. The algorithm is publicly available as open-source software.Comment: 6 figures, 2 table

Distinguishing Topical and Social Groups Based on Common Identity and Bond Theory

Social groups play a crucial role in social media platforms because they form the basis for user participation and engagement. Groups are created explicitly by members of the community, but also form organically as members interact. Due to their importance, they have been studied widely (e.g., community detection, evolution, activity, etc.). One of the key questions for understanding how such groups evolve is whether there are different types of groups and how they differ. In Sociology, theories have been proposed to help explain how such groups form. In particular, the common identity and common bond theory states that people join groups based on identity (i.e., interest in the topics discussed) or bond attachment (i.e., social relationships). The theory has been applied qualitatively to small groups to classify them as either topical or social. We use the identity and bond theory to define a set of features to classify groups into those two categories. Using a dataset from Flickr, we extract user-defined groups and automatically-detected groups, obtained from a community detection algorithm. We discuss the process of manual labeling of groups into social or topical and present results of predicting the group label based on the defined features. We directly validate the predictions of the theory showing that the metrics are able to forecast the group type with high accuracy. In addition, we present a comparison between declared and detected groups along topicality and sociality dimensions.Comment: 10 pages, 6 figures, 2 table

Complex networks approach to modeling online social systems. The emergence of computational social science

This thesis is devoted to quantitative description, analysis, and modeling of complex social systems in the form of online social networks. Statistical patterns of the systems under study are unveiled and interpreted using concepts and methods of network science, social network analysis, and data mining. A long-term promise of this research is that predicting the behavior of complex techno-social systems will be possible in a way similar to contemporary weather forecasting, using statistical inference and computational modeling based on the advancements in understanding and knowledge of techno-social systems. Although the subject of this study are humans, as opposed to atoms or molecules in statistical physics, the availability of extremely large datasets on human behavior permits the use of tools and techniques of statistical physics. This dissertation deals with large datasets from online social networks, measures statistical patterns of social behavior, and develops quantitative methods, models, and metrics for complex techno-social systemsLa presente tesis está dedicada a la descripción, análisis y modelado cuantitativo de sistemas complejos sociales en forma de redes sociales en internet. Mediante el uso de métodos y conceptos provenientes de ciencia de redes, análisis de redes sociales y minería de datos se descubren diferentes patrones estadísticos de los sistemas estudiados. Uno de los objetivos a largo plazo de esta línea de investigación consiste en hacer posible la predicción del comportamiento de sistemas complejos tecnológico-sociales, de un modo similar a la predicción meteorológica, usando inferencia estadística y modelado computacional basado en avances en el conocimiento de los sistemas tecnológico-sociales. A pesar de que el objeto del presente estudio son seres humanos, en lugar de los átomos o moléculas estudiados tradicionalmente en la física estadística, la disponibilidad de grandes bases de datos sobre comportamiento humano hace posible el uso de técnicas y métodos de física estadística. En el presente trabajo se utilizan grandes bases de datos provenientes de redes sociales en internet, se miden patrones estadísticos de comportamiento social, y se desarrollan métodos cuantitativos, modelos y métricas para el estudio de sistemas complejos tecnológico-sociales

Resilience of Supervised Learning Algorithms to Discriminatory Data Perturbations

Discrimination is a focal concern in supervised learning algorithms augmenting human decision-making. These systems are trained using historical data, which may have been tainted by discrimination, and may learn biases against the protected groups. An important question is how to train models without propagating discrimination. In this study, we i) define and model discrimination as perturbations of a data-generating process and show how discrimination can be induced via attributes correlated with the protected attributes; ii) introduce a measure of resilience of a supervised learning algorithm to potentially discriminatory data perturbations, iii) propose a novel supervised learning algorithm that inhibits discrimination, and iv) show that it is more resilient to discriminatory perturbations in synthetic and real-world datasets than state-of-the-art learning algorithms. The proposed method can be used with general supervised learning algorithms and avoids inducement of discrimination, while maximizing model accuracy.Comment: 17 pages, 10 figures, 1 tabl

Kobieta w wieku 58 lat z bólem w klatce piersiowej

We present the case of a 58-year-old woman with suspected myocardial infarction. Coronarography did not reveal changes in coronary arteries. Laboratory tests revealed increases in troponin and inflammation parameters, and therefore MRI was performed. This showed subendocardial ischaemic necrosis with organ viability preservation in the heart muscle. As a result, myocardial infarction with non obstructive coronary arteries (MINOCA) was diagnosed.Przedstawiono opis przypadku 58-letniej pacjentki z podejrzeniem zawału serca. Weryfikacja koronarograficzna niepotwierdziła zmian w naczyniach wieńcowych. Ze względu na wzrost parametrów stanu zapalnego i markerów martwicymięśnia sercowego w badaniach laboratoryjnych wykonano badanie rezonansu magnetycznego serca, na którym uwidoczniono podwsierdziowe ogniska martwicy z zachowaniem żywotności w mięśniu sercowym, co pozwoliło rozpoznaćzawał serca bez zmian w naczyniach wieńcowych (MINOCA)

The Road to Popularity: The Dilution of Growing Audience on Twitter

On social media platforms, like Twitter, users are often interested in gaining more influence and popularity by growing their set of followers, aka their audience. Several studies have described the properties of users on Twitter based on static snapshots of their follower network. Other studies have analyzed the general process of link formation. Here, rather than investigating the dynamics of this process itself, we study how the characteristics of the audience and follower links change as the audience of a user grows in size on the road to user's popularity. To begin with, we find that the early followers tend to be more elite users than the late followers, i.e., they are more likely to have verified and expert accounts. Moreover, the early followers are significantly more similar to the person that they follow than the late followers. Namely, they are more likely to share time zone, language, and topics of interests with the followed user. To some extent, these phenomena are related with the growth of Twitter itself, wherein the early followers tend to be the early adopters of Twitter, while the late followers are late adopters. We isolate, however, the effect of the growth of audiences consisting of followers from the growth of Twitter's user base itself. Finally, we measure the engagement of such audiences with the content of the followed user, by measuring the probability that an early or late follower becomes a retweeter

The Passions of Bohdan Krawciw

Slavic Languages and Literature

Taras Shevchenko: The Making of the National Poet

Given his iconic function as National Poet, the process of Shevchenko’s actual emergence into this role has not received adequate attention; for the most part it has been replaced by an implied teleology. In one sense this was true.With its unprecedented energy, openness to the collective experience, to deeper archetypal symbolism and to a problematization of the poet’s psyche, his poetry was also a form of self-fashioning—which could not but be felt by his readership.This was reinforced by the major events of his life: the success of his early poetry and his enthusiastic reception in Ukraine, his arrest and exile (1847-1857), and then his triumphal return to St. Petersburg as spokesman and generally acknowledged representative of the nascent national movement and its literature. Arguably, the key moment in imprinting the paradigm of Shevchenko as national martyr and poet were the immediate responses to his death by his friends and fellow members in the Brotherhood of Sts. Cyril and Methodius, Pantelejmon Kulish and Mykola Kostomarov, who couched their grief and their vision in a numinous mode, implicitly articulating an all but religious sense of the poet-as-prophet.Pour avoir été largement placé dans une perspective implicitement téléologique, le processus par lequel Taras Ševčenko a acquis son statut de figure iconique nationale n’a pas été examiné avec suffisamment d’attention. Il y a des raisons à cela. Avec son énergie sans précédent, son ouverture à l’expérience collective, à un symbolisme archétypal plus profond, à une problématisation de la psychè du poète, sa poésie est également une forme de façonnement de soi, ce qui ne pouvait pas échapper à ses lecteurs. Tout cela a été renforcé par les événements majeurs de sa vie : le succès de sa poésie des débuts et sa réception enthousiaste en Ukraine, son arrestation et son exil (1847-1857), son retour triomphal à Saint-Pétersbourg en tant que porte-parole et représentant généralement reconnu du mouvement national naissant et de sa littérature. Vraisemblablement, les bases du paradigme faisant de Ševčenko un poète et martyr national ont été posées par ses amis et membres de la Confrérie Cyril et Méthode, Pantelejmon Kuliš et Mykola Kostomarov, qui, juste après sa mort, ont exprimé leur douleur et leur vision de façon déroutante, énonçant implicitement un sentiment non religieux du poète-prophète