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Found 56 papers, 13 papers with code
COVID-19 in Bulgarian Social Media: Factuality, Harmfulness, Propaganda, and Framing
With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic.
MIPD: Exploring Manipulation and Intention In a Novel Corpus of Polish Disinformation
This study presents a novel corpus of 15, 356 Polish web articles, including articles identified as containing disinformation.
ArAIEval Shared Task: Persuasion Techniques and Disinformation Detection in Arabic Text
We present an overview of the ArAIEval shared task, organized as part of the first ArabicNLP 2023 conference co-located with EMNLP 2023.
Temporal Dynamics of Coordinated Online Behavior: Stability, Archetypes, and Influence
Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of coordinated online behavior.
Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabic
Thus, there has been a lot of recent research on automatic detection of propaganda techniques in text as well as in memes.
Detecting and Understanding Harmful Memes: A Survey
One interesting finding is that many types of harmful memes are not really studied, e. g., such featuring self-harm and extremism, partly due to the lack of suitable datasets.
The Spread of Propaganda by Coordinated Communities on Social Media
Large-scale manipulations on social media have two important characteristics: (i) use of propaganda to influence others, and (ii) adoption of coordinated behavior to spread it and to amplify its impact.
Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claims
We present an overview of the second edition of the CheckThat!
Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News
We describe the fourth edition of the CheckThat!
Findings of the NLP4IF-2021 Shared Tasks on Fighting the COVID-19 Infodemic and Censorship Detection
Here, we present the tasks, analyze the results, and discuss the system submissions and the methods they used.
A Second Pandemic? Analysis of Fake News About COVID-19 Vaccines in Qatar
While COVID-19 vaccines are finally becoming widely available, a second pandemic that revolves around the circulation of anti-vaxxer fake news may hinder efforts to recover from the first one.
Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document
The output is a re-ranked list of the document sentences, so that those that can be verified are ranked as high as possible, together with corresponding evidence.
Interpretable Propaganda Detection in News Articles
Online users today are exposed to misleading and propagandistic news articles and media posts on a daily basis.
Detecting Propaganda Techniques in Memes
We further create and release a new corpus of 950 memes, carefully annotated with 22 propaganda techniques, which can appear in the text, in the image, or in both.
SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images
We describe SemEval-2021 task 6 on Detection of Persuasion Techniques in Texts and Images: the data, the annotation guidelines, the evaluation setup, the results, and the participating systems.
The Role of Context in Detecting Previously Fact-Checked Claims
Recent years have seen the proliferation of disinformation and fake news online.
A Survey on Multimodal Disinformation Detection
As a result, researchers started leveraging different modalities and combinations thereof to tackle online multimodal offensive content.
Automated Fact-Checking for Assisting Human Fact-Checkers
The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism.
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
We present the results and the main findings of SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles.
Fact-Checking, Fake News, Propaganda, and Media Bias: Truth Seeking in the Post-Truth Era
The rise of social media has democratized content creation and has made it easy for everybody to share and spread information online.
We Can Detect Your Bias: Predicting the Political Ideology of News Articles
We explore the task of predicting the leading political ideology or bias of news articles.
Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models
While misinformation and disinformation have been thriving in social media for years, with the emergence of the COVID-19 pandemic, the political and the health misinformation merged, thus elevating the problem to a whole new level and giving rise to the first global infodemic.
Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media
The first four tasks compose the full pipeline of claim verification in social media: Task 1 on check-worthiness estimation, Task 2 on retrieving previously fact-checked claims, Task 3 on evidence retrieval, and Task 4 on claim verification.
Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms
With the outbreak of the COVID-19 pandemic, people turned to social media to read and to share timely information including statistics, warnings, advice, and inspirational stories.
A Survey on Computational Propaganda Detection
Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda.
Prta: A System to Support the Analysis of Propaganda Techniques in the News
However, little attention has been paid to the specific rhetorical and psychological techniques used to convey propaganda messages.
That is a Known Lie: Detecting Previously Fact-Checked Claims
Interestingly, despite the importance of the task, it has been largely ignored by the research community so far.
Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society
With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic.
CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media
Finally, the lab offers a fifth task that asks to predict the check-worthiness of the claims made in English political debates and speeches.
Proppy: A System to Unmask Propaganda in Online News
We present proppy, the first publicly available real-world, real-time propaganda detection system for online news, which aims at raising awareness, thus potentially limiting the impact of propaganda and helping fight disinformation.
Global Thread-Level Inference for Comment Classification in Community Question Answering
Community question answering, a recent evolution of question answering in the Web context, allows a user to quickly consult the opinion of a number of people on a particular topic, thus taking advantage of the wisdom of the crowd.
Experiments in Detecting Persuasion Techniques in the News
Many recent political events, like the 2016 US Presidential elections or the 2018 Brazilian elections have raised the attention of institutions and of the general public on the role of Internet and social media in influencing the outcome of these events.
Fine-Grained Analysis of Propaganda in News Article
Propaganda aims at influencing people{'}s mindset with the purpose of advancing a specific agenda.
Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detection
FLC is a fragment-level task that asks for the identification of propagandist text fragments in a news article and also for the prediction of the specific propaganda technique used in each such fragment (18-way classification task).
Fine-Grained Analysis of Propaganda in News Articles
Propaganda aims at influencing people's mindset with the purpose of advancing a specific agenda.
Tanbih: Get To Know What You Are Reading
We introduce Tanbih, a news aggregator with intelligent analysis tools to help readers understanding what's behind a news story.
Team Jack Ryder at SemEval-2019 Task 4: Using BERT Representations for Detecting Hyperpartisan News
We describe the system submitted by the Jack Ryder team to SemEval-2019 Task 4 on Hyperpartisan News Detection.
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.
A Flexible, Efficient and Accurate Framework for Community Question Answering Pipelines
Although deep neural networks have been proving to be excellent tools to deliver state-of-the-art results, when data is scarce and the tackled tasks involve complex semantic inference, deep linguistic processing and traditional structure-based approaches, such as tree kernel methods, are an alternative solution.
Cross-Language Question Re-Ranking
We compare a kernel-based system with a feed-forward neural network in a scenario where a large parallel corpus is available for training a machine translation system, bilingual dictionaries, and cross-language word embeddings.
Building Chatbots from Forum Data: Model Selection Using Question Answering Metrics
Finally, we propose to use extrinsic evaluation with respect to a QA task as an automatic evaluation method for chatbots.
The Impact of Modeling Overall Argumentation with Tree Kernels
Several approaches have been proposed to model either the explicit sequential structure of an argumentative text or its implicit hierarchical structure.
KeLP at SemEval-2017 Task 3: Learning Pairwise Patterns in Community Question Answering
This paper describes the KeLP system participating in the SemEval-2017 community Question Answering (cQA) task.
An Interactive System for Exploring Community Question Answering Forums
We present an interactive system to provide effective and efficient search capabilities in Community Question Answering (cQA) forums.
Selecting Sentences versus Selecting Tree Constituents for Automatic Question Ranking
Community question answering (cQA) websites are focused on users who query questions onto an online forum, expecting for other users to provide them answers or suggestions.
Neural Attention for Learning to Rank Questions in Community Question Answering
In real-world data, e. g., from Web forums, text is often contaminated with redundant or irrelevant content, which leads to introducing noise in machine learning algorithms.
Addressing Community Question Answering in English and Arabic
In the case of the Arabic question re-ranking task, for the first time we applied tree kernels on syntactic trees of Arabic sentences.
Graph Kernels exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions
In this paper we present a novel graph kernel framework inspired the by the Weisfeiler-Lehman (WL) isomorphism tests.
A tree-based kernel for graphs with continuous attributes
While existing kernel methods are effective techniques for dealing with graphs having discrete node labels, their adaptation to non-discrete or continuous node attributes has been limited, mainly for computational issues.
Ordered Decompositional DAG Kernels Enhancements
In this paper, we show how the Ordered Decomposition DAGs (ODD) kernel framework, a framework that allows the definition of graph kernels from tree kernels, allows to easily define new state-of-the-art graph kernels.
An Empirical Study on Budget-Aware Online Kernel Algorithms for Streams of Graphs
It turns out that, when strict memory budget constraints have to be enforced, working in feature space, given the current state of the art on graph kernels, is more than a viable alternative to dual approaches, both in terms of speed and classification performance.
