Search Results for author: Giovanni Da San Martino

Found 52 papers, 12 papers with code

COVID-19 in Bulgarian Social Media: Factuality, Harmfulness, Propaganda, and Framing

1 code implementation RANLP 2021 Preslav Nakov, Firoj Alam, Shaden Shaar, Giovanni Da San Martino, Yifan Zhang

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.


Detecting and Understanding Harmful Memes: A Survey

1 code implementation9 May 2022 Shivam Sharma, Firoj Alam, Md. Shad Akhtar, Dimitar Dimitrov, Giovanni Da San Martino, Hamed Firooz, Alon Halevy, Fabrizio Silvestri, Preslav Nakov, Tanmoy Chakraborty

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

no code implementations27 Sep 2021 Kristina Hristakieva, Stefano Cresci, Giovanni Da San Martino, Mauro Conti, Preslav Nakov

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.

A Second Pandemic? Analysis of Fake News About COVID-19 Vaccines in Qatar

no code implementations RANLP 2021 Preslav Nakov, Firoj Alam, Shaden Shaar, Giovanni Da San Martino, Yifan Zhang

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.

Detecting Propaganda Techniques in Memes

1 code implementation ACL 2021 Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, Firoj Alam, Fabrizio Silvestri, Hamed Firooz, Preslav Nakov, Giovanni Da San Martino

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

1 code implementation SEMEVAL 2021 Dimitar Dimitrov, Bishr Bin Ali, Shaden Shaar, Firoj Alam, Fabrizio Silvestri, Hamed Firooz, Preslav Nakov, Giovanni Da San Martino

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.

Automated Fact-Checking for Assisting Human Fact-Checkers

no code implementations13 Mar 2021 Preslav Nakov, David Corney, Maram Hasanain, Firoj Alam, Tamer Elsayed, Alberto Barrón-Cedeño, Paolo Papotti, Shaden Shaar, Giovanni Da San Martino

The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism.

Fact Checking

Fact-Checking, Fake News, Propaganda, and Media Bias: Truth Seeking in the Post-Truth Era

no code implementations EMNLP 2020 Preslav Nakov, Giovanni Da San Martino

The rise of social media has democratized content creation and has made it easy for everybody to share and spread information online.

Fact Checking Misinformation

Team Alex at CLEF CheckThat! 2020: Identifying Check-Worthy Tweets With Transformer Models

3 code implementations7 Sep 2020 Alex Nikolov, Giovanni Da San Martino, Ivan Koychev, Preslav Nakov

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.

Fact Checking Misinformation

Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms

1 code implementation15 Jul 2020 Firoj Alam, Fahim Dalvi, Shaden Shaar, Nadir Durrani, Hamdy Mubarak, Alex Nikolov, Giovanni Da San Martino, Ahmed Abdelali, Hassan Sajjad, Kareem Darwish, Preslav Nakov

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

no code implementations15 Jul 2020 Giovanni Da San Martino, Stefano Cresci, Alberto Barron-Cedeno, Seunghak Yu, Roberto Di Pietro, Preslav Nakov

Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda.

Propaganda detection

Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media

3 code implementations15 Jul 2020 Alberto Barron-Cedeno, Tamer Elsayed, Preslav Nakov, Giovanni Da San Martino, Maram Hasanain, Reem Suwaileh, Fatima Haouari, Nikolay Babulkov, Bayan Hamdan, Alex Nikolov, Shaden Shaar, Zien Sheikh Ali

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.

Proppy: A System to Unmask Propaganda in Online News

no code implementations14 Dec 2019 Alberto Barrón-Cedeño, Giovanni Da San Martino, Israa Jaradat, Preslav Nakov

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.

Propaganda detection

Global Thread-Level Inference for Comment Classification in Community Question Answering

no code implementations EMNLP 2015 Shafiq Joty, Alberto Barrón-Cedeño, Giovanni Da San Martino, Simone Filice, Lluís Màrquez, Alessandro Moschitti, Preslav Nakov

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.

Community Question Answering General Classification

Experiments in Detecting Persuasion Techniques in the News

no code implementations15 Nov 2019 Seunghak Yu, Giovanni Da San Martino, Preslav Nakov

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.

Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detection

no code implementations WS 2019 Giovanni Da San Martino, Alberto Barrón-Cedeño, Preslav Nakov

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).

General Classification Propaganda detection

A Flexible, Efficient and Accurate Framework for Community Question Answering Pipelines

no code implementations ACL 2018 Salvatore Romeo, Giovanni Da San Martino, Alberto Barr{\'o}n-Cede{\~n}o, Aless Moschitti, ro

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.

Community Question Answering

Cross-Language Question Re-Ranking

no code implementations4 Oct 2017 Giovanni Da San Martino, Salvatore Romeo, Alberto Barron-Cedeno, Shafiq Joty, Lluis Marquez, Alessandro Moschitti, Preslav Nakov

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.

Machine Translation Re-Ranking +1

The Impact of Modeling Overall Argumentation with Tree Kernels

no code implementations EMNLP 2017 Henning Wachsmuth, Giovanni Da San Martino, Dora Kiesel, Benno Stein

Several approaches have been proposed to model either the explicit sequential structure of an argumentative text or its implicit hierarchical structure.

General Classification Text Classification

Selecting Sentences versus Selecting Tree Constituents for Automatic Question Ranking

no code implementations COLING 2016 Alberto Barr{\'o}n-Cede{\~n}o, Giovanni Da San Martino, Salvatore Romeo, Aless Moschitti, ro

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.

Community Question Answering Machine Translation

Graph Kernels exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensions

no code implementations22 Sep 2015 Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti

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

no code implementations3 Sep 2015 Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti

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

no code implementations13 Jul 2015 Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti

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.

General Classification

An Empirical Study on Budget-Aware Online Kernel Algorithms for Streams of Graphs

no code implementations8 Jul 2015 Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti

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.

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