Cross-Lingual Classification of Crisis Data

Many citizens nowadays flock to social media during crises to share or acquire the latest information about the event. Due to the sheer volume of data typically circulated during such events, it is necessary to be able to efficiently filter out irrelevant posts, thus focusing attention on the posts that are truly relevant to the crisis. Current methods for classifying the relevance of posts to a crisis or set of crises typically struggle to deal with posts in different languages, and it is not viable during rapidly evolving crisis situations to train new models for each language. In this paper we test statistical and semantic classification approaches on cross-lingual datasets from 30 crisis events, consisting of posts written mainly in English, Spanish, and Italian. We experiment with scenarios where the model is trained on one language and tested on another, and where the data is translated to a single language. We show that the addition of semantic features extracted from external knowledge bases improve accuracy over a purely statistical model

Tracking Machine Learning Bias Creep in Traditional and Online Lending Systems with Covariance Analysis

Machine Learning (ML) algorithms are embedded within online banking services, proposing decisions about consumers’ credit cards, car loans, and mortgages. These algorithms are sometimes biased, resulting in unfair decisions toward certain groups. One common approach for addressing such bias is simply dropping the sensitive attributes from the training data (e.g. gender). However, sensitive attributes can indirectly be represented by other attributes in the data (e.g. maternity leave taken). This paper addresses the problem of identifying attributes that can mimic sensitive attributes by proposing a new approach based on covariance analysis. Our evaluation conducted on two different credit datasets, extracted from a traditional and an online banking institution respectively, shows how our approach: (i) effectively identifies the attributes from the data that encapsulate sensitive information and, (ii) leads to the reduction of biases in ML models, while maintaining their overall performance

The Fact-Checking Observatory: Reporting the Co-Spread of Misinformation and Fact-checks on Social Media

In the context of the Covid-19 pandemic and the Russian invasion of Ukraine, tracking how misinformation and fact-checks spread on social media is key for understanding where fact-checking efforts need to be focused and what demographics are most likely to spread misinformation. In this article, we introduce the Fact-checking Observatory, a website that automatically generates human-readable weekly reports about the spread of misinformation and fact-checks on Twitter. The proposed approach differs from other tools that give one-off manual reports or visualisation by providing organisations and individuals with easily readable and shareable self-contained reports that contain both information about the spread of misinformation and fact-checks

Demographics and topics impact on the co-spread of COVID-19 misinformation and fact-checks on Twitter

Correcting misconceptions and false beliefs are important for injecting reliable information about COVID-19 into public discourse, but what impact does this have on the continued proliferation of misinforming claims? Fact-checking organisations produce content with the aim of reducing misinformation spread, but our knowledge of its impact on misinformation for particular topics and demographics is limited. In this article, we explore the relation between misinformation and fact-checking spread during the COVID-19 pandemic for different topics, user demographics and attributes. We specifically follow misinformation and fact-checks emerging from December 2019 until the 4th of January 2021 on Twitter. Using a combination of spread variance analysis, impulse response modelling and causal analysis, we highlight the bidirectional, weak causation spread behaviour between misinformation and fact-checks. Although we observe that fact-checks about COVID-19 are appearing fairly quickly after misinformation is circulated, its ability to reduce overall misinformation spread appears to be limited. This is especially visible for misinformation about conspiracy theories and the causes of the virus

Adaptation of cryo-sectioning for immuno-EM-labeling of asymmetric samples: a study using C. elegans.

International audienceCryo-sectioning procedures, initially develop by Tokuyasu have been successfully improved for tissues and cultured cells, enabling efficient protein localization on the ultrastructural level. Without a standard procedure applicable to any sample, currently existing protocols must be individually modified for each model organism or asymmetric sample. Here, we describe our method that enables reproducible cryo-sectioning of C. elegans larvae/adults and embryos. We have established a chemical fixation procedure in which flat embedding considerably simplifies manipulation and lateral orientation of larvae or adults. To bypass the limitations of chemical fixation, we have improved the hybrid cryo-immobilization-rehydration technique, and reduced the overall time required to complete this procedure. Using our procedures precise cryo-sectioning orientation can be combined with good ultrastructural preservation and efficient immuno-electron microscopy protein localization. Also, GFP fluorescence can be efficiently preserved, permitting a direct correlation of the fluorescent signal and its subcellular localization. Though developed for C. elegans samples, our method addresses the challenge of working with small asymmetric samples in general, and thus could be used to improve the efficiency of immuno-electron localization in other model organisms

Successful Thrombectomy Improves Functional Outcome in Tandem Occlusions with a Large Ischemic Core

International audienceBackground: Emergent stenting in tandem occlusions and mechanical thrombectomy (MT) of acute ischemic stroke related to large vessel occlusion (LVO-AIS) with a large core are tested independently. We aim to assess the impact of reperfusion with MT in patients with LVO-AIS with a large core and a tandem occlusion and to compare the safety of reperfusion between large core with tandem and nontandem occlusions in current practice. Methods: We analyzed data of all consecutive patients included in the prospective Endovascular Treatment in Ischemic Stroke Registry in France between January 2015 and March 2023 who presented with a pretreatment ASPECTS (Alberta Stroke Program Early CT Score) of 0–5 and angiographically proven tandem occlusion. The primary end point was a favorable outcome defined by a modified Rankin Scale (mRS) score of 0–3 at 90 days. Results: Among 262 included patients with a tandem occlusion and ASPECTS 0–5, 203 patients (77.5%) had a successful reperfusion (modified Thrombolysis in Cerebral Infarction grade 2b-3). Reperfused patients had a favorable shift in the overall mRS score distribution (adjusted odds ratio [aOR], 1.57 [1.22–2.03]; P < 0.001), higher rates of mRS score 0–3 (aOR, 7.03 [2.60–19.01]; P < 0.001) and mRS score 0–2 at 90 days (aOR, 3.85 [1.39–10.68]; P = 0.009) compared with nonreperfused. There was a trend between the occurrence of successful reperfusion and a decreased rate of symptomatic intracranial hemorrhage (aOR, 0.5 [0.22–1.13]; P = 0.096). Similar safety outcomes were observed after large core reperfusion in tandem and nontandem occlusions. Conclusions: Successful reperfusion was associated with a higher rate of favorable outcome in large core LVO-AIS with a tandem occlusion, with a safety profile similar to nontandem occlusion

Mechanical Thrombectomy for Acute Ischemic Stroke Amid the COVID-19 Outbreak

International audienceBackground and Purpose: The efficiency of prehospital care chain response and the adequacy of hospital resources are challenged amid the coronavirus disease 2019 (COVID-19) outbreak, with suspected consequences for patients with ischemic stroke eligible for mechanical thrombectomy (MT). Methods: We conducted a prospective national-level data collection of patients treated with MT, ranging 45 days across epidemic containment measures instatement, and of patients treated during the same calendar period in 2019. The primary end point was the variation of patients receiving MT during the epidemic period. Secondary end points included care delays between onset, imaging, and groin puncture. To analyze the primary end point, we used a Poisson regression model. We then analyzed the correlation between the number of MTs and the number of COVID-19 cases hospitalizations, using the Pearson correlation coefficient (compared with the null value). Results: A total of 1513 patients were included at 32 centers, in all French administrative regions. There was a 21% significant decrease (0.79; [95%CI, 0.76–0.82]; P <0.001) in MT case volumes during the epidemic period, and a significant increase in delays between imaging and groin puncture, overall (mean 144.9±SD 86.8 minutes versus 126.2±70.9; P <0.001 in 2019) and in transferred patients (mean 182.6±SD 82.0 minutes versus 153.25±67; P <0.001). After the instatement of strict epidemic mitigation measures, there was a significant negative correlation between the number of hospitalizations for COVID and the number of MT cases ( R 2 −0.51; P =0.04). Patients treated during the COVID outbreak were less likely to receive intravenous thrombolysis and to have unwitnessed strokes (both P <0.05). Conclusions: Our study showed a significant decrease in patients treated with MTs during the first stages of the COVID epidemic in France and alarming indicators of lengthened care delays. These findings prompt immediate consideration of local and regional stroke networks preparedness in the varying contexts of COVID-19 pandemic evolution