On the Role of Images for Analyzing Claims in Social Media

Fake news is a severe problem in social media. In this paper, we present an empirical study on visual, textual, and multimodal models for the tasks of claim, claim check-worthiness, and conspiracy detection, all of which are related to fake news detection... (read more)

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Methods used in the Paper


METHOD TYPE
Batch Normalization
Normalization
Average Pooling
Pooling Operations
1x1 Convolution
Convolutions
ReLU
Activation Functions
Max Pooling
Pooling Operations
Global Average Pooling
Pooling Operations
Bottleneck Residual Block
Skip Connection Blocks
Residual Block
Skip Connection Blocks
Kaiming Initialization
Initialization
Convolution
Convolutions
ResNet
Convolutional Neural Networks
Residual Connection
Skip Connections
Weight Decay
Regularization
Attention Dropout
Regularization
Linear Warmup With Linear Decay
Learning Rate Schedules
WordPiece
Subword Segmentation
Adam
Stochastic Optimization
Dropout
Regularization
Softmax
Output Functions
Dense Connections
Feedforward Networks
GELU
Activation Functions
Multi-Head Attention
Attention Modules
Layer Normalization
Normalization
Scaled Dot-Product Attention
Attention Mechanisms
BERT
Language Models
ViLBERT
Representation Learning