True scale-free networks hidden by finite size effects

We analyze about two hundred naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statistical testing of the validity of power law distributions of network degrees by contrasting real data. Specifically, we analyze by finite-size scaling analysis the datasets of real networks to check whether purported departures from the power law behavior are due to the finiteness of the sample size. In this case, power laws would be recovered in the case of progressively larger cutoffs induced by the size of the sample. We find that a large number of the networks studied follow a finite size scaling hypothesis without any self-tuning. This is the case of biological protein interaction networks, technological computer and hyperlink networks, and informational networks in general. Marked deviations appear in other cases, especially infrastructure and transportation but also social networks. We conclude that underlying scale invariance properties of many naturally occurring networks are extant features often clouded by finite-size effects due to the nature of the sample data

Hallermann–Streiff syndrome with severe bilateral enophthalmos and radiological evidence of silent brain syndrome: a new congenital silent brain syndrome?

BACKGROUND: We present the first case of a congenital form of silent brain syndrome (SBS) in a young patient affected by Hallermann-Streiff syndrome (HSS) and the surgical management of the associated eyelid anomalies. METHODS: HSS signs were evaluated according to the Francois criteria. Orbital computed tomography (CT) and genetic analysis were performed. An upper eyelid retractor-free recession was performed. Follow-up visits were performed at day 1, weeks 1 and 3, and months 3, 6, 9 (for both eyes), and 12 (for left eye) after surgery. RESULTS: The patient exhibited six of the seven signs of HSS. Orbital CT showed bilateral enophthalmos and upward bowing of the orbital roof with air entrapment under the upper eyelid as previously described for SBS. Genetic analysis showed a 2q polymorphism. During follow-up, the cornea showed absence of epithelial damage and the upper eyelids were lowered symmetrically, with a regular contour. CONCLUSION: Our HSS patient shares features with SBS. We postulate that SBS could include more than one pattern, ie, an acquired form following ventriculoperitoneal shunting and this newly reported congenital form in our HSS patient in whom typical syndromic skull anomalies led to this condition. The surgical treatment has been effective in restoring an appropriate lid level, with good globe apposition and a good cosmetic result

Why polls fail to predict elections

In the past decade we have witnessed the failure of traditional polls in predicting presidential election outcomes across the world. To understand the reasons behind these failures we analyze the raw data of a trusted pollster which failed to predict, along with the rest of the pollsters, the surprising 2019 presidential election in Argentina which has led to a major market collapse in that country. Analysis of the raw and re-weighted data from longitudinal surveys performed before and after the elections reveals clear biases (beyond well-known low-response rates) related to mis-representation of the population and, most importantly, to social-desirability biases, i.e., the tendency of respondents to hide their intention to vote for controversial candidates. We then propose a longitudinal opinion tracking method based on big-data analytics from social media, machine learning, and network theory that overcomes the limits of traditional polls. The model achieves accurate results in the 2019 Argentina elections predicting the overwhelming victory of the candidate Alberto Fern\'andez over the president Mauricio Macri; a result that none of the traditional pollsters in the country was able to predict. Beyond predicting political elections, the framework we propose is more general and can be used to discover trends in society; for instance, what people think about economics, education or climate change.Comment: 47 pages, 10 tables, 15 figure

Suspended accounts align with the Internet Research Agency misinformation campaign to influence the 2016 US election

Abstract The ongoing debate surrounding the impact of the Internet Research Agency’s (IRA) social media campaign during the 2016 U.S. presidential election has largely overshadowed the involvement of other actors. Our analysis brings to light a substantial group of suspended Twitter users, outnumbering the IRA user group by a factor of 60, who align with the ideologies of the IRA campaign. Our study demonstrates that this group of suspended Twitter accounts significantly influenced individuals categorized as undecided or weak supporters, potentially with the aim of swaying their opinions, as indicated by Granger causality

The Role of the IRA in Twitter during the 2016 US Presidential Election: Unveiling Amplification and Influence of Suspended Accounts

The impact of the social media campaign conducted by the Internet Research Agency (IRA) during the 2016 U.S. presidential election continues to be a topic of ongoing debate. While it is widely acknowledged that the objective of this campaign was to support Donald Trump, the true extent of its influence on Twitter users remains uncertain. Previous research has primarily focused on analyzing the interactions between IRA users and the broader Twitter community to assess the campaign's impact. In this study, we propose an alternative perspective that suggests the existing approach may underestimate the true extent of the IRA campaign. Our analysis uncovers the presence of a notable group of suspended Twitter users, whose size surpasses the IRA user group size by a factor of 60. These suspended users exhibit close interactions with IRA accounts, suggesting potential collaboration or coordination. Notably, our findings reveal the significant role played by these previously unnoticed accounts in amplifying the impact of the IRA campaign, surpassing even the reach of the IRA accounts themselves by a factor of 10. In contrast to previous findings, our study reveals that the combined efforts of the Internet Research Agency (IRA) and the identified group of suspended Twitter accounts had a significant influence on individuals categorized as undecided or weak supporters, probably with the intention of swaying their opinions.Comment: 13 Tables, 12 Figure

Biased news sharing and partisan polarization on social media

In the ever-connected digital landscape, news dissemination on social media platforms serves as a vital source of information for the public. However, this flow of information is far from unbiased. It is deeply influenced by the political inclinations of the users who share news as well as the inherent biases present in the news outlets themselves. These biases in news consumption play a significant role in the creation of echo chambers and the reinforcement of beliefs. This phenomenon, in turn, influences the voting intentions of the population during critical electoral periods. In this study, we use a metric called "Sentiment Bias", a tool designed to classify news outlets according to their biases. We explore the impact of this metric on various levels, ranging from news outlets to individual user biases. Our metric, while simple, unveils a well-known trend: users prefer news aligning with their political beliefs. Its power lies in extending this insight to specific topics. Users consistently share articles related to subjects that echo their favored candidates, illuminating a deeper layer of political alignment in online discourse

Is the short posterior stabilization by TLIF and cages a good way for a correct spinal alignment in the de novo scoliosis? A case report

De novo scoliosis is becoming one of the most prevalent findings in the aging spine, and this condition is associated not only with severe back or leg symptoms but also with complicated surgical outcomes. The most common surgery is a posterior spinal fusion with metal implants and bone graft (from the pelvis or the bone bank), with or without decompression of the nerve roots. Sometimes the surgery may need to be performed anteriorly (from the front of the spine) for better stability, correction, and healing. After 1 years of follow, up we presented a case report of a 74 year old man treated for De Novo Scoliosis with a spinal short posterior stabilization, TLIF and Cages

The hidden dimension of information diffusion: A latent space representation of Social Media News Sharing behavior

In times marked by an abundance of news sources and the widespread use of social media for staying informed, acquiring accurate data faces increasing challenges. Today, access to information plays a crucial role in shaping public opinion and is significantly influenced by interactions on social media. Therefore, studying the dissemination of news on these platforms is vital for understanding how individuals stay informed. In this paper, we study emergent properties of media outlet sharing behavior by users in social media. We quantify this behavior in terms of coordinates in a latent space proposing a metric called Media Sharing Index (MSI). We observe that the MSI shows a bimodal distribution in this latent dimension, reflecting the preference of large groups of users for specific groups of media outlets. This methodology allows the study of the extent to which communities of interacting users are permeable to different sources of information. Additionally, it facilitates the analysis of the relationship between users' media outlet preferences, their political leanings, and the political leanings of the media outlets