Papers by Ramy Baly
We Can Detect Your Bias: Predicting the Political Ideology of News Articles (2020.emnlp-main)
Copied to clipboard
| Challenge: | a new study examines the role of media in predicting political ideology or bias in news articles . systematic exposure to bias in the news can foster intolerance and ideological segregation . |
| Approach: | They propose an adversarial media adaptation and a specially adapted triplet loss for predicting political ideology in news articles. |
| Outcome: | The proposed model improves over state-of-the-art models in this challenging setup. |
Integrating Stance Detection and Fact Checking in a Unified Corpus (N18-2)
Copied to clipboard
| Challenge: | Existing methods for fact checking are not supported by existing datasets, which treat fact checking, document retrieval, source credibility, stance detection and rationale extraction as independent tasks. |
| Approach: | They propose to implement automatic fact checking on an Arabic fact checking corpus, which is the first of its kind. |
| Outcome: | The proposed approach is based on an Arabic fact checking corpus, the first of its kind. |
Predicting Factuality of Reporting and Bias of News Media Sources (D18-1)
Copied to clipboard
| Challenge: | a new study examines the factuality of news media and its biases . social media has democratized content creation and spread information online . |
| Approach: | They propose to characterize entire news media to predict factuality and bias . they experiment with news websites and a set of features derived from their content . |
| Outcome: | The proposed model shows that the features of news websites perform better than baseline . the results show that the feature types are important for fact-checking systems . |
Tanbih: Get To Know What You Are Reading (D19-3)
Copied to clipboard
Yifan Zhang, Giovanni Da San Martino, Alberto Barrón-Cedeño, Salvatore Romeo, Jisun An, Haewoon Kwak, Todor Staykovski, Israa Jaradat, Georgi Karadzhov, Ramy Baly, Kareem Darwish, James Glass, Preslav Nakov
| Challenge: | Nowadays, more and more readers consume news online. |
| Approach: | They propose a news platform that displays news grouped into events and generates media profiles that show the general factuality of reporting, the degree of propagandistic content, hyper-partisanship, leading political ideology, general frame of reporting and stance with respect to various claims and topics of a media outlet. |
| Outcome: | The proposed news platform displays news grouped into events and generates media profiles that show the factuality of reporting, the degree of propagandistic content, hyper-partisanship, leading political ideology, general frame of reporting and stance with respect to various claims and topics of a news outlet. |
Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Media (N19-1)
Copied to clipboard
| Challenge: | a number of fact-checking initiatives have been launched, both manual and automatic, but the whole enterprise remains in a state of crisis. |
| Approach: | They propose a multi-task ordinal regression framework that models trustworthiness estimation and political ideology detection of entire news outlets. |
| Outcome: | The proposed model outperforms models that target the problems in isolation. |
What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context (2020.acl-main)
Copied to clipboard
Ramy Baly, Georgi Karadzhov, Jisun An, Haewoon Kwak, Yoan Dinkov, Ahmed Ali, James Glass, Preslav Nakov
| Challenge: | a growing number of fake news reports are published online, causing a trust crisis . a new study aims to predict political bias and factuality of reporting of entire news outlets . |
| Approach: | They propose to profile entire news outlets and look for those that are likely to publish fake content . they also examine what was written about the target medium and who reads it . |
| Outcome: | The proposed method improves on the current state-of-the-art in analyzing social media and what was written about the target medium. |
Automatic Stance Detection Using End-to-End Memory Networks (N18-1)
Copied to clipboard
| Challenge: | Existing methods for fact checking are tedious and often broken into intermediate steps to alleviate complexity. |
| Approach: | They propose an end-to-end memory network model that predicts whether a document can be considered relevant for a given claim and extracts relevant text snippets. |
| Outcome: | The proposed model predicts whether a document can be considered relevant for a given claim and extracts relevant text snippets to reason about the factuality of the target claim. |