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相关论文: ArAIEval Shared Task: Propagandistic Techniques De…

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The spread of propaganda through the internet has increased drastically over the past years. Lately, propaganda detection has started gaining importance because of the negative impact it has on society. In this work, we describe our…

计算与语言 · 计算机科学 2022-10-21 Tanmay Chavan , Aditya Kane

In this paper, we describe our approach to utilize pre-trained BERT models with Convolutional Neural Networks for sub-task A of the Multilingual Offensive Language Identification shared task (OffensEval 2020), which is a part of the SemEval…

计算与语言 · 计算机科学 2020-07-28 Ali Safaya , Moutasem Abdullatif , Deniz Yuret

Memes are one of the most popular types of content used to spread information online. They can influence a large number of people through rhetorical and psychological techniques. The task, Detection of Persuasion Techniques in Texts and…

计算与语言 · 计算机科学 2021-06-02 Kshitij Gupta , Devansh Gautam , Radhika Mamidi

The proliferation of multimodal content on social media presents significant challenges in understanding and moderating complex, context-dependent issues such as misinformation, hate speech, and propaganda. While efforts have been made to…

计算与语言 · 计算机科学 2026-03-03 Mohamed Bayan Kmainasi , Abul Hasnat , Md Arid Hasan , Ali Ezzat Shahroor , Firoj Alam

Women are influential online, especially in image-based social media such as Twitter and Instagram. However, many in the network environment contain gender discrimination and aggressive information, which magnify gender stereotypes and…

计算与语言 · 计算机科学 2022-04-21 Da Li , Ming Yi , Yukai He

This paper presents our strategy to tackle the EACL WANLP-2021 Shared Task 2: Sarcasm and Sentiment Detection. One of the subtasks aims at developing a system that identifies whether a given Arabic tweet is sarcastic in nature or not, while…

计算与语言 · 计算机科学 2021-03-03 Anshul Wadhawan

The expanding financial markets of the Arab world require sophisticated Arabic NLP tools. To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) shared task proposes two subtasks: (i) Multi-dialect Intent…

This paper describes our submissions to SemEval 2020 Task 11: Detection of Propaganda Techniques in News Articles for each of the two subtasks of Span Identification and Technique Classification. We make use of pre-trained BERT language…

计算与语言 · 计算机科学 2020-07-23 Paramansh Singh , Siraj Sandhu , Subham Kumar , Ashutosh Modi

This paper describes our approach to hierarchical multi-label detection of persuasion techniques in meme texts. Our model, developed as a part of the recent SemEval task, is based on fine-tuning individual language models (BERT,…

计算与语言 · 计算机科学 2024-07-04 Kota Shamanth Ramanath Nayak , Leila Kosseim

We describe our approach for SemEval-2021 task 6 on detection of persuasion techniques in multimodal content (memes). Our system combines pretrained multimodal models (CLIP) and chained classifiers. Also, we propose to enrich the data by a…

计算与语言 · 计算机科学 2021-06-01 Erfan Ghadery , Damien Sileo , Marie-Francine Moens

Misinformation spreading in mainstream and social media has been misleading users in different ways. Manual detection and verification efforts by journalists and fact-checkers can no longer cope with the great scale and quick spread of…

计算与语言 · 计算机科学 2023-05-08 Maram Hasanain , Ahmed Oumar El-Shangiti , Rabindra Nath Nandi , Preslav Nakov , Firoj Alam

This paper describes our participation in the SemEval-2020 task Detection of Propaganda Techniques in News Articles. We participate in both subtasks: Span Identification (SI) and Technique Classification (TC). We use a bi-LSTM architecture…

计算与语言 · 计算机科学 2020-08-25 Verena Blaschke , Maxim Korniyenko , Sam Tureski

We present the results and the main findings of SemEval-2019 Task 6 on Identifying and Categorizing Offensive Language in Social Media (OffensEval). The task was based on a new dataset, the Offensive Language Identification Dataset (OLID),…

计算与语言 · 计算机科学 2019-04-30 Marcos Zampieri , Shervin Malmasi , Preslav Nakov , Sara Rosenthal , Noura Farra , Ritesh Kumar

Since the introduction of the SemEval 2020 Task 11 (Martino et al., 2020a), several approaches have been proposed in the literature for classifying propaganda based on the rhetorical techniques used to influence readers. These methods,…

计算与语言 · 计算机科学 2023-06-01 Anni Chen , Bhuwan Dhingra

The experimental landscape in natural language processing for social media is too fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics like sentiment analysis to irony detection or emoji prediction.…

计算与语言 · 计算机科学 2020-10-27 Francesco Barbieri , Jose Camacho-Collados , Leonardo Neves , Luis Espinosa-Anke

In this paper we present our approach and the system description for Sub-task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media. Sub-task A involves identifying if a given tweet is…

计算与语言 · 计算机科学 2019-04-22 Haimin Zhang , Debanjan Mahata , Simra Shahid , Laiba Mehnaz , Sarthak Anand , Yaman Singla , Rajiv Ratn Shah , Karan Uppal

We present the shared task on Fine-Grained Propaganda Detection, which was organized as part of the NLP4IF workshop at EMNLP-IJCNLP 2019. There were two subtasks. FLC is a fragment-level task that asks for the identification of propagandist…

计算与语言 · 计算机科学 2019-10-23 Giovanni Da San Martino , Alberto Barrón-Cedeño , Preslav Nakov

This paper summarizes our studies on propaganda detection techniques for news articles in the SemEval-2020 task 11. This task is divided into the SI and TC subtasks. We implemented the GloVe word representation, the BERT pretraining model,…

计算与语言 · 计算机科学 2020-08-26 Jiaxu Dao , Jin Wang , Xuejie Zhang

Online presence on social media platforms such as Facebook and Twitter has become a daily habit for internet users. Despite the vast amount of services the platforms offer for their users, users suffer from cyber-bullying, which further…

计算与语言 · 计算机科学 2022-07-19 Ahmad Shapiro , Ayman Khalafallah , Marwan Torki

The Large Language Models (LLMs) exhibit remarkable ability to generate fluent content across a wide spectrum of user queries. However, this capability has raised concerns regarding misinformation and personal information leakage. In this…