Developing a Natural Language Understanding Model to Characterize Cable News Bias

Media bias has been extensively studied by both social and computational sciences. However, current work still has a large reliance on human input and subjective assessment to label biases. This is especially true for cable news research. To address these issues, we develop an unsupervised machine learning method to characterize the bias of cable news programs without any human input. This method relies on the analysis of what topics are mentioned through Named Entity Recognition and how those topics are discussed through Stance Analysis in order to cluster programs with similar biases together. Applying our method to 2020 cable news transcripts, we find that program clusters are consistent over time and roughly correspond to the cable news network of the program. This method reveals the potential for future tools to objectively assess media bias and characterize unfamiliar media environments

Mapping State-Sponsored Information Operations with Multi-View Modularity Clustering

This paper presents a new computational framework for mapping state-sponsored information operations into distinct strategic units. Utilizing a novel method called multi-view modularity clustering (MVMC), we identify groups of accounts engaged in distinct narrative and network information maneuvers. We then present an analytical pipeline to holistically determine their coordinated and complementary roles within the broader digital campaign. Applying our proposed methodology to disclosed Chinese state-sponsored accounts on Twitter, we discover an overarching operation to protect and manage Chinese international reputation by attacking individual adversaries (Guo Wengui) and collective threats (Hong Kong protestors), while also projecting national strength during global crisis (the COVID-19 pandemic). Psycholinguistic tools quantify variation in narrative maneuvers employing hateful and negative language against critics in contrast to communitarian and positive language to bolster national solidarity. Network analytics further distinguish how groups of accounts used network maneuvers to act as balanced operators, organized masqueraders, and egalitarian echo-chambers. Collectively, this work breaks methodological ground on the interdisciplinary application of unsupervised and multi-view methods for characterizing not just digital campaigns in particular, but also coordinated activity more generally. Moreover, our findings contribute substantive empirical insights around how state-sponsored information operations combine narrative and network maneuvers to achieve interlocking strategic objectives. This bears both theoretical and policy implications for platform regulation and understanding the evolving geopolitical significance of cyberspace

Use of Large Language Models for Stance Classification

Stance detection, the task of predicting an author's viewpoint towards a subject of interest, has long been a focal point of research. Current stance detection methods predominantly rely on manual annotation of sentences, followed by training a supervised machine learning model. This manual annotation process, however, imposes limitations on the model's ability to fully comprehend the stances in the sentence and hampers its potential to generalize across different contexts. In this study, we investigate the use of Large Language Models (LLMs) for the task of stance classification, with an absolute minimum use of human labels. We scrutinize four distinct types of prompting schemes combined with LLMs, comparing their accuracies with manual stance determination. Our study reveals that while LLMs can match or sometimes even exceed the benchmark results in each dataset, their overall accuracy is not definitively better than what can be produced by supervised models. This suggests potential areas for improvement in the stance classification for LLMs. The application of LLMs, however, opens up promising avenues for unsupervised stance detection, thereby curtailing the need for manual collection and annotation of stances. This not only streamlines the process but also paves the way for expanding stance detection capabilities across languages. Through this paper, we shed light on the stance classification abilities of LLMs, thereby contributing valuable insights that can guide future advancements in this domain.Comment: Submitted to ICWSM 2024. 9 pages, plus appendix and 1 figur

High-sensitivity troponin and the application of risk stratification thresholds in patients with suspected acute coronary syndrome

Background: Guidelines acknowledge the emerging role of high-sensitivity cardiac troponin (hs-cTnl) for risk stratification and the early rule-out of myocardial infarction, but multiple thresholds have been described. We evaluate the safety and effectiveness of risk stratification thresholds in patients with suspected acute coronary syndrome. Methods: Consecutive patients with suspected acute coronary syndrome (n=48 282) were enrolled in a multicenter trial across 10 hospitals in Scotland. In a prespecified secondary and observational analysis, we compared the performance of the limit of detection (<2 ng/L) and an optimized risk stratification threshold (<5 ng/L) using the Abbott high-sensitivity troponin I assay. Patients with myocardial injury at presentation, with ≤2 hours of symptoms or with ST-segment elevation myocardial infarction were excluded. The negative predictive value was determined in all patients and in subgroups for a primary outcome of myocardial infarction or cardiac death within 30 days. The secondary outcome was myocardial infarction or cardiac death at 12 months, with risk modeled using logistic regression adjusted for age and sex. Results: In total, 32 837 consecutive patients (61±17 years, 47% female) were included, of whom 23 260 (71%) and 12,716 (39%) had hs-cTnl concentrations of <5 ng/L and <2 ng/L at presentation. The negative predictive value for the primary outcome was 99.8% (95% CI, 99.7%–99.8%) and 99.9% (95% CI, 99.8%–99.9%) in those with hs-cTnl concentrations of <5 ng/L and <2 ng/L, respectively. At both thresholds, the negative predictive value was consistent in men and women and across all age groups, although the proportion of patients identified as low risk fell with increasing age. Compared with patients with hs-cTnl concentrations of ≥5 ng/L but <99th centile, the risk of myocardial infarction or cardiac death at 12 months was 77% lower in those <5 ng/L (5.3% vs 0.7%; adjusted odds ratio, 0.23 [95% CI, 0.19–0.28]) and 80% lower in those <2 ng/L (5.3% vs 0.3%; adjusted odds ratio, 0.20 [95% CI, 0.14–0.29]). Conclusions: Use of risk stratification thresholds for hs-cTnl identify patients with suspected acute coronary syndrome and at least 2 hours of symptoms as low risk at presentation irrespective of age and sex

From bits to bites: Advancement of the Germinate platform to support prebreeding informatics for crop wild relatives

Management and distribution of experimental data from prebreeding projects is important to ensure uptake of germplasm into breeding and research programs. Being able to access and share this data in standard formats is essential. The adoption of a common informatics platform for crops that may have limited resources brings economies of scale, allowing common informatics components to be used across multiple species. The close integration of such a platform with commonly used breeding software, visualization, and analysis tools reduces the barrier for entry to researchers and provides a common framework to facilitate collaborations and data sharing. This work presents significant updates to the Germinate platform and highlights its value in distributing prebreeding data for 14 crops as part of the project ‘Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives’ (hereafter Crop Trust Crop Wild Relatives project) led by the Crop Trust (https://www.cwrdiversity.org). The addition of data on these species compliments data already publicly available in Germinate. We present a suite of updated Germinate features using examples from these crop species and their wild relatives. The use of Germinate within the Crop TrustCropWildRelatives project demonstrates the usefulness of the system and the benefits a shared informatics platform provides. These data resources provide a foundation on which breeding and research communities can develop additional online resources for their crops, harness new data as it becomes available, and benefit collectively from future developments of the Germinate platform

High-sensitivity troponin in the evaluation of patients with suspected acute coronary syndrome: a stepped-wedge, cluster-randomised controlled trial.

BACKGROUND: High-sensitivity cardiac troponin assays permit use of lower thresholds for the diagnosis of myocardial infarction, but whether this improves clinical outcomes is unknown. We aimed to determine whether the introduction of a high-sensitivity cardiac troponin I (hs-cTnI) assay with a sex-specific 99th centile diagnostic threshold would reduce subsequent myocardial infarction or cardiovascular death in patients with suspected acute coronary syndrome. METHODS: In this stepped-wedge, cluster-randomised controlled trial across ten secondary or tertiary care hospitals in Scotland, we evaluated the implementation of an hs-cTnI assay in consecutive patients who had been admitted to the hospitals' emergency departments with suspected acute coronary syndrome. Patients were eligible for inclusion if they presented with suspected acute coronary syndrome and had paired cardiac troponin measurements from the standard care and trial assays. During a validation phase of 6-12 months, results from the hs-cTnI assay were concealed from the attending clinician, and a contemporary cardiac troponin I (cTnI) assay was used to guide care. Hospitals were randomly allocated to early (n=5 hospitals) or late (n=5 hospitals) implementation, in which the high-sensitivity assay and sex-specific 99th centile diagnostic threshold was introduced immediately after the 6-month validation phase or was deferred for a further 6 months. Patients reclassified by the high-sensitivity assay were defined as those with an increased hs-cTnI concentration in whom cTnI concentrations were below the diagnostic threshold on the contemporary assay. The primary outcome was subsequent myocardial infarction or death from cardiovascular causes at 1 year after initial presentation. Outcomes were compared in patients reclassified by the high-sensitivity assay before and after its implementation by use of an adjusted generalised linear mixed model. This trial is registered with ClinicalTrials.gov, number NCT01852123. FINDINGS: Between June 10, 2013, and March 3, 2016, we enrolled 48 282 consecutive patients (61 [SD 17] years, 47% women) of whom 10 360 (21%) patients had cTnI concentrations greater than those of the 99th centile of the normal range of values, who were identified by the contemporary assay or the high-sensitivity assay. The high-sensitivity assay reclassified 1771 (17%) of 10 360 patients with myocardial injury or infarction who were not identified by the contemporary assay. In those reclassified, subsequent myocardial infarction or cardiovascular death within 1 year occurred in 105 (15%) of 720 patients in the validation phase and 131 (12%) of 1051 patients in the implementation phase (adjusted odds ratio for implementation vs validation phase 1·10, 95% CI 0·75 to 1·61; p=0·620). INTERPRETATION: Use of a high-sensitivity assay prompted reclassification of 1771 (17%) of 10 360 patients with myocardial injury or infarction, but was not associated with a lower subsequent incidence of myocardial infarction or cardiovascular death at 1 year. Our findings question whether the diagnostic threshold for myocardial infarction should be based on the 99th centile derived from a normal reference population. FUNDING: The British Heart Foundation

Effectiveness of a national quality improvement programme to improve survival after emergency abdominal surgery (EPOCH): a stepped-wedge cluster-randomised trial

Background: Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. Methods: We did a stepped-wedge cluster-randomised trial of patients aged 40 years or older undergoing emergency open major abdominal surgery. Eligible UK National Health Service (NHS) hospitals (those that had an emergency general surgical service, a substantial volume of emergency abdominal surgery cases, and contributed data to the National Emergency Laparotomy Audit) were organised into 15 geographical clusters and commenced the QI programme in a random order, based on a computer-generated random sequence, over an 85-week period with one geographical cluster commencing the intervention every 5 weeks from the second to the 16th time period. Patients were masked to the study group, but it was not possible to mask hospital staff or investigators. The primary outcome measure was mortality within 90 days of surgery. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN80682973. Findings: Treatment took place between March 3, 2014, and Oct 19, 2015. 22 754 patients were assessed for elegibility. Of 15 873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 patients in the usual care group and 7374 in the QI group. Eight patients in the usual care group and nine patients in the QI group were not included in the analysis because of missing primary outcome data. The primary outcome of 90-day mortality occurred in 1210 (16%) patients in the QI group compared with 1393 (16%) patients in the usual care group (HR 1·11, 0·96–1·28). Interpretation: No survival benefit was observed from this QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. Future QI programmes should ensure that teams have both the time and resources needed to improve patient care. Funding: National Institute for Health Research Health Services and Delivery Research Programme

Effectiveness of a national quality improvement programme to improve survival after emergency abdominal surgery (EPOCH): a stepped-wedge cluster-randomised trial

BACKGROUND: Emergency abdominal surgery is associated with poor patient outcomes. We studied the effectiveness of a national quality improvement (QI) programme to implement a care pathway to improve survival for these patients. METHODS: We did a stepped-wedge cluster-randomised trial of patients aged 40 years or older undergoing emergency open major abdominal surgery. Eligible UK National Health Service (NHS) hospitals (those that had an emergency general surgical service, a substantial volume of emergency abdominal surgery cases, and contributed data to the National Emergency Laparotomy Audit) were organised into 15 geographical clusters and commenced the QI programme in a random order, based on a computer-generated random sequence, over an 85-week period with one geographical cluster commencing the intervention every 5 weeks from the second to the 16th time period. Patients were masked to the study group, but it was not possible to mask hospital staff or investigators. The primary outcome measure was mortality within 90 days of surgery. Analyses were done on an intention-to-treat basis. This study is registered with the ISRCTN registry, number ISRCTN80682973. FINDINGS: Treatment took place between March 3, 2014, and Oct 19, 2015. 22 754 patients were assessed for elegibility. Of 15 873 eligible patients from 93 NHS hospitals, primary outcome data were analysed for 8482 patients in the usual care group and 7374 in the QI group. Eight patients in the usual care group and nine patients in the QI group were not included in the analysis because of missing primary outcome data. The primary outcome of 90-day mortality occurred in 1210 (16%) patients in the QI group compared with 1393 (16%) patients in the usual care group (HR 1·11, 0·96-1·28). INTERPRETATION: No survival benefit was observed from this QI programme to implement a care pathway for patients undergoing emergency abdominal surgery. Future QI programmes should ensure that teams have both the time and resources needed to improve patient care. FUNDING: National Institute for Health Research Health Services and Delivery Research Programme