Rumors may bring a negative impact on social life, and compared with pure textual rumors, online rumors multiple modalities at the same time are more likely to mislead users spread, so multimodal rumor detection cannot be ignored. Current methods for do not focus fusion of text picture-region object features, we propose neural network TDEDA (dual-attention based double embedding) applied detect...

This study aims to explore the time series context and sentiment polarity features of rumors’ life cycles, how use them optimize CNN model parameters improve classification effect. The proposed is a convolutional neural network embedded with an attention mechanism information. Firstly, whole cycle rumors divided into 20 groups by algorithm each group texts trained Doc2Vec obtain text vector. Se...

Fear that the Internet promotes harmful political rumoring is merited but not for reasons originally anticipated. Although the network accelerates and widens rumor circulation, on the whole, it does not increase recipient credulity. E-mail, however, which fosters informal political communication within existing social networks, poses a unique threat to factual political knowledge. A national te...

An infodemic often involving rumors, stigma,and conspiracy theories has been prevalent during the COVID-19 pandemic. Social media data monitoring identified as best method for tracking rumors in real-timeand a possible way to dispel misinformation and reduce stigma. However, identifying, assessing,and responding real-timeis complex task. Disinformation fueled by hearsay, can have potentially se...