Automatic Stance Detection Using End-to-End Memory Networks

We present a novel end-to-end memory network for stance detection, which jointly (i) predicts whether a document agrees, disagrees, discusses or is unrelated with respect to a given target claim, and also (ii) extracts snippets of evidence for that prediction. The network operates at the paragraph level and integrates convolutional and recurrent neural networks, as well as a similarity matrix as part of the overall architecture. The experimental evaluation on the Fake News Challenge dataset shows state-of-the-art performance.Comment: NAACL-2018; Stance detection; Fact-Checking; Veracity; Memory networks; Neural Networks; Distributed Representation

Fact Checking in Community Forums

Community Question Answering (cQA) forums are very popular nowadays, as they represent effective means for communities around particular topics to share information. Unfortunately, this information is not always factual. Thus, here we explore a new dimension in the context of cQA, which has been ignored so far: checking the veracity of answers to particular questions in cQA forums. As this is a new problem, we create a specialized dataset for it. We further propose a novel multi-faceted model, which captures information from the answer content (what is said and how), from the author profile (who says it), from the rest of the community forum (where it is said), and from external authoritative sources of information (external support). Evaluation results show a MAP value of 86.54, which is 21 points absolute above the baseline.Comment: AAAI-2018; Fact-Checking; Veracity; Community-Question Answering; Neural Networks; Distributed Representation

FROM SEMANTIC TO EMOTIONAL SPACE IN SENSE SENTIMENT ANALYSIS

Ph.DDOCTOR OF PHILOSOPH

Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection

In this paper, we describe our submission to SemEval-2019 Task 4 on Hyperpartisan News Detection. Our system relies on a variety of engineered features originally used to detect propaganda. This is based on the assumption that biased messages are propagandistic in the sense that they promote a particular political cause or viewpoint. We trained a logistic regression model with features ranging from simple bag-of-words to vocabulary richness and text readability features. Our system achieved 72.9% accuracy on the test data that is annotated manually and 60.8% on the test data that is annotated with distant supervision. Additional experiments showed that significant performance improvements can be achieved with better feature pre-processing.Comment: Hyperpartisanship, propaganda, news media, fake news, SemEval-201

The Sudden Death of a Pregnant Woman With Takotsubo Cardiomyopathy Following a Legal Abortion: A Case Report

Background: Takotsubo cardiomyopathy (TCM) is characterized by left ventricular dysfunction and apical ballooning due to physical or mental stress in the absence of coronary artery disease. This transient heart disorder is rare in pregnancy. It may affect women of reproductive age.Case Presentation: The case was a 38-year-old woman in the first trimester of pregnancy with a history of TCM diagnosis one year ago, admitted to the hospital for a legal abortion. At the time of hospitalization, echo cardiography, echo cardiography, and clinical tests results were normal; however, due to stressful factors, such as the cancellation of the dilation & curettage (D&C) procedure, despite being transferred to the operating room (due to the absence of a gynecologist), receiving misoprostol for two consecutive days, the prolongation of surgery time, as well as the absence of a psychiatrist to reduce stress during the operation, suffered from recurrent TCM and eventually expired. In the autopsy, the cause of death was a massive pulmonary embolism.Conclusion: In pregnant women, there is a possibility of TCM recurrence due to changes in hormonal levels and emotional and physical stress caused by pregnancy. Therefore, when performing a surgical procedure such as D&C, a team consisting of gynecologists, cardiologists, and psychiatrists should be present to avoid dangerous complications such as sudden death

Epidemiology of orthopedic trauma in children and adolescent in a referral center in Tehran: A prospective study

Background: Orthopedic trauma is a common type of injury in children and may cause deep and permanent psychological and physical damage both for the patient and the parents. This study aimed to analyze the epidemiology age, gender distribution and the mechanism of injury in patients presenting to a level I trauma center in urban population of Tehran. Methods: In this prospective descriptive study, the patients under 19 years old with orthopedic trauma who were hospitalized in Tehran Shafa University Hospital were entered. This hospital is the main orthopedic referral center in Iran. The patients were prospectively evaluated from April 2013 to March 2014. The data were collected and analyzed. Results: The study included 1081 patients under 19 years old. There was a male predominance (76.8 n= 830). The boys had a higher mean age 11.04±5.06 year, versus girls with mean age 8.67±4.63 year (P< 0.05). The peak age of boys was 18 and the girls had two peaks at three and nine. The fractures occurred in upper limb in 70.8 (n= 621) and 29.2 (n= 256) in lower limb of patients. There were 27 cases with joint dislocation, 5 cases with knee ligamentous injuries, 128 cases with soft tissue injuries and 44 cases with spine injuries. The most frequent mechanism in both gender were falls from standing position (48.5). The most common fractures were foreman both bone fractures (n: 146 16.7), elbow supracondylar fractures (n: 134, 15.3) and distal radius fractures (n: 84, 9.6). The most fractures occurred in summer (30.1) and the least in winter (18.1). Conclusion: Evaluation of epidemiologic factors can lead to the best prediction and treatment planning of trauma. Early recognition of injury, even minor, and expected care using specialized teams will help to improve outcomes for these patients. This study determines the most at risk children for trauma and fractures and may help the parents to prevent damage. © 2015, Tehran University of Medical Sciences. All rights reserved