Quantifying Transient Spreading Dynamics on Networks

Spreading phenomena on networks are essential for the collective dynamics of various natural and technological systems, from information spreading in gene regulatory networks to neural circuits or from epidemics to supply networks experiencing perturbations. Still, how local disturbances spread across networks is not yet quantitatively understood. Here we analyze generic spreading dynamics in deterministic network dynamical systems close to a given operating point. Standard dynamical systems' theory does not explicitly provide measures for arrival times and amplitudes of a transient, spreading signal because it focuses on invariant sets, invariant measures and other quantities less relevant for transient behavior. We here change the perspective and introduce effective expectation values for deterministic dynamics to work out a theory explicitly quantifying when and how strongly a perturbation initiated at one unit of a network impacts any other. The theory provides explicit timing and amplitude information as a function of the relative position of initially perturbed and responding unit as well as on the entire network topology.Comment: 9 pages and 4 figures main manuscript 9 pages and 3 figures appendi

QUOTUS: The Structure of Political Media Coverage as Revealed by Quoting Patterns

Given the extremely large pool of events and stories available, media outlets need to focus on a subset of issues and aspects to convey to their audience. Outlets are often accused of exhibiting a systematic bias in this selection process, with different outlets portraying different versions of reality. However, in the absence of objective measures and empirical evidence, the direction and extent of systematicity remains widely disputed. In this paper we propose a framework based on quoting patterns for quantifying and characterizing the degree to which media outlets exhibit systematic bias. We apply this framework to a massive dataset of news articles spanning the six years of Obama's presidency and all of his speeches, and reveal that a systematic pattern does indeed emerge from the outlet's quoting behavior. Moreover, we show that this pattern can be successfully exploited in an unsupervised prediction setting, to determine which new quotes an outlet will select to broadcast. By encoding bias patterns in a low-rank space we provide an analysis of the structure of political media coverage. This reveals a latent media bias space that aligns surprisingly well with political ideology and outlet type. A linguistic analysis exposes striking differences across these latent dimensions, showing how the different types of media outlets portray different realities even when reporting on the same events. For example, outlets mapped to the mainstream conservative side of the latent space focus on quotes that portray a presidential persona disproportionately characterized by negativity.Comment: To appear in the Proceedings of WWW 2015. 11pp, 10 fig. Interactive visualization, data, and other info available at http://snap.stanford.edu/quotus

Loyalty in Online Communities

Loyalty is an essential component of multi-community engagement. When users have the choice to engage with a variety of different communities, they often become loyal to just one, focusing on that community at the expense of others. However, it is unclear how loyalty is manifested in user behavior, or whether loyalty is encouraged by certain community characteristics. In this paper we operationalize loyalty as a user-community relation: users loyal to a community consistently prefer it over all others; loyal communities retain their loyal users over time. By exploring this relation using a large dataset of discussion communities from Reddit, we reveal that loyalty is manifested in remarkably consistent behaviors across a wide spectrum of communities. Loyal users employ language that signals collective identity and engage with more esoteric, less popular content, indicating they may play a curational role in surfacing new material. Loyal communities have denser user-user interaction networks and lower rates of triadic closure, suggesting that community-level loyalty is associated with more cohesive interactions and less fragmentation into subgroups. We exploit these general patterns to predict future rates of loyalty. Our results show that a user's propensity to become loyal is apparent from their first interactions with a community, suggesting that some users are intrinsically loyal from the very beginning.Comment: Extended version of a paper appearing in the Proceedings of ICWSM 2017 (with the same title); please cite the official ICWSM versio

Redox Regulation of NLRP3 Inflammasomes: ROS as Trigger or Effector?

Significance: Inflammasomes are multiprotein complexes localized within the cytoplasm of the cell that are responsible for the maturation of proinflammatory cytokines such as interleukin-1β (IL-1β) and IL-18, and the activation of a highly inflammatory form of cell death, pyroptosis. In response to infection or cellular stress, inflammasomes are assembled, activated, and involved in host defense and pathophysiology of diseases. Clarification of the molecular mechanisms leading to the activation of this intracellular inflammatory machinery may provide new insights into the concept of inflammation as the root of and route to human diseases. Recent Advances: The activation of inflammasomes, specifically the most fully characterized inflammasome—the nucleotide-binding oligomerization domain (NOD)-like receptor containing pyrin domain 3 (NLRP3) inflammasome, is now emerging as a critical molecular mechanism for many degenerative diseases. Several models have been developed to describe how NLRP3 inflammasomes are activated, including K+ efflux, lysosome function, endoplasmic reticulum (ER) stress, intracellular calcium, ubiquitination, microRNAs, and, in particular, reactive oxygen species (ROS). Critical Issues: ROS may serve as a “kindling” or triggering factor to activate NLRP3 inflammasomes as well as “bonfire” or “effector” molecules, resulting in pathological processes. Increasing evidence seeks to understand how this spatiotemporal action of ROS occurs during NLRP3 inflammasome activation, which will be a major focus of this review. Future Directions: It is imperative to know how this dual action of ROS works during NLRP3 inflammation activation on different stimuli and what relevance such spatiotemporal redox regulation of NLRP3 inflammasomes has in cell or organ functions and possible human diseases

What changed your mind : the roles of dynamic topics and discourse in argumentation process

In our world with full of uncertainty, debates and argumentation contribute to the progress of science and society. Despite of the in- creasing attention to characterize human arguments, most progress made so far focus on the debate outcome, largely ignoring the dynamic patterns in argumentation processes. This paper presents a study that automatically analyzes the key factors in argument persuasiveness, beyond simply predicting who will persuade whom. Specifically, we propose a novel neural model that is able to dynamically track the changes of latent topics and discourse in argumentative conversations, allowing the investigation of their roles in influencing the outcomes of persuasion. Extensive experiments have been conducted on argumentative conversations on both social media and supreme court. The results show that our model outperforms state-of-the-art models in identifying persuasive arguments via explicitly exploring dynamic factors of topic and discourse. We further analyze the effects of topics and discourse on persuasiveness, and find that they are both useful -- topics provide concrete evidence while superior discourse styles may bias participants, especially in social media arguments. In addition, we draw some findings from our empirical results, which will help people better engage in future persuasive conversations

Phosphorylation of the Mdm2 oncoprotein by the c-Abl tyrosine kinase regulates p53 tumor suppression and the radiosensitivity of mice

The p53 tumor suppressor acts as a guardian of the genome by preventing the propagation of DNA damage-induced breaks and mutations to subsequent generations of cells. We have previously shown that phosphorylation of the Mdm2 oncoprotein at Ser394 by the ATM kinase is required for robust p53 stabilization and activation in cells treated with ionizing radiation, and that loss of Mdm2 Ser394 phosphorylation leads to spontaneous tumorigenesis and radioresistance in Mdm2S394A mice. Previous in vitro data indicate that the c-Abl kinase phosphorylates Mdm2 at the neighboring residue (Tyr393) in response to DNA damage to regulate p53-dependent apoptosis. In this present study, we have generated an Mdm2 mutant mouse (Mdm2Y393F) to determine whether c-Abl phosphorylation of Mdm2 regulates the p53-mediated DNA damage response or p53 tumor suppression in vivo. The Mdm2Y393F mice develop accelerated spontaneous and oncogene-induced tumors, yet display no defects in p53 stabilization and activity following acute genotoxic stress. Although apoptosis is unaltered in these mice, they recover more rapidly from radiation-induced bone marrow ablation and are more resistant to whole-body radiation-induced lethality. These data reveal an in vivo role for c-Abl phosphorylation of Mdm2 in regulation of p53 tumor suppression and bone marrow failure. However, c-Abl phosphorylation of Mdm2 Tyr393 appears to play a lesser role in governing Mdm2-p53 signaling than ATM phosphorylation of Mdm2 Ser394. Furthermore, the effects of these phosphorylation events on p53 regulation are not additive, as Mdm2Y393F/S394A mice and Mdm2S394A mice display similar phenotypes