Identifying multimodal misinformation leveraging novelty detection and emotion recognition [0.03%]
基于新颖性检测和情感识别的跨模态误导信息检测研究
Rina Kumari,Nischal Ashok,Pawan Kumar Agrawal et al.
Rina Kumari et al.
With the growing presence of multimodal content on the web, a specific category of fake news is rampant on popular social media outlets. In this category of fake online information, real multimedia contents (images, videos) are used in diff...
Multilingual deep learning framework for fake news detection using capsule neural network [0.03%]
基于胶囊神经网络的多语言深度学习假新闻检测框架
Rami Mohawesh,Sumbal Maqsood,Qutaibah Althebyan
Rami Mohawesh
Fake news detection is an essential task; however, the complexity of several languages makes fake news detection challenging. It requires drawing many conclusions about the numerous people involved to comprehend the logic behind some fake s...
Yihong Zhang,Masumi Shirakawa,Takahiro Hara
Yihong Zhang
Given the recent availability of large volumes of social media discussions, finding temporal unusual phenomena, which can be called events, from such data is of great interest. Previous works on social media event detection either assume a ...
Towards a soft three-level voting model (Soft T-LVM) for fake news detection [0.03%]
面向假新闻检测的软三等级投票模型(Soft T-LVM)
Boutheina Jlifi,Chayma Sakrani,Claude Duvallet
Boutheina Jlifi
Fake news has a worldwide impact and the potential to change political scenarios and human behavior, especially in a critical time like the COVID-19 pandemic. This work suggests a Soft Three-Level Voting Model (Soft T-LVM) for automatically...
Multi-class classification of COVID-19 documents using machine learning algorithms [0.03%]
使用机器学习算法进行COVID-19文献的多分类识别
Gollam Rabby,Petr Berka
Gollam Rabby
In most biomedical research paper corpus, document classification is a crucial task. Even due to the global epidemic, it is a crucial task for researchers across a variety of fields to figure out the relevant scientific research papers accu...
An image and text-based multimodal model for detecting fake news in OSN's [0.03%]
基于图像和文本的多模式模型，用于检测OSN中的假新闻
Santosh Kumar Uppada,Parth Patel,Sivaselvan B
Santosh Kumar Uppada
Digital Mass Media has become the new paradigm of communication that revolves around online social networks. The increase in the utilization of online social networks (OSNs) as the primary source of information and the increase of online so...
Detecting COVID-19 vaccine hesitancy in India: a multimodal transformer based approach [0.03%]
基于多模态变换器的印度新冠疫苗犹豫检测方法
Anindita Borah
Anindita Borah
COVID-19 has emerged as the greatest threat in recent times, causing extensive mortality and morbidity in the entire world. India is among the highly affected countries suffering severe disruptions due this pandemic. To overcome the adverse...
Deep learning based sentiment analysis of public perception of working from home through tweets [0.03%]
基于深度学习的居家办公公众感知情感分析研究
Aarushi Vohra,Ritu Garg
Aarushi Vohra
Nowadays, we are witnessing a paradigm shift from the conventional approach of working from office spaces to the emerging culture of working virtually from home. Even during the COVID-19 pandemic, many organisations were forced to allow emp...
Multi-task learning for toxic comment classification and rationale extraction [0.03%]
用于毒舌评论分类和原因提取的多任务学习方法
Kiran Babu Nelatoori,Hima Bindu Kommanti
Kiran Babu Nelatoori
Social media content moderation is the standard practice as on today to promote healthy discussion forums. Toxic span prediction is helpful for explaining the toxic comment classification labels, thus is an important step towards building a...
Germán Braun,Pablo Rubén Fillottrani,C Maria Keet
Germán Braun
Complex system development and maintenance face the challenge of dealing with different types of models due to language affordances, preferences, sizes, and so forth that involve interaction between users with different levels of proficienc...