A novel hybrid deep learning model for detecting covid-19-related rumors on social media based on lstm and concatenated parallel cnns

Mohammed Al-Sarem; Abdullah Alsaeedi; Faisal Saeed; Wadii Boulila; Omair Ameerbakhsh

doi:10.3390/APP11177940

A novel hybrid deep learning model for detecting covid-19-related rumors on social media based on lstm and concatenated parallel cnns

Mohammed Al-Sarem^*, Abdullah Alsaeedi^*, Faisal Saeed^*, Wadii Boulila, Omair Ameerbakhsh

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

56 Citations (SciVal)

Original language	English
Article number	7940
Journal	Applied Sciences (Switzerland)
Volume	11
Issue number	17
DOIs	https://doi.org/10.3390/APP11177940
Publication status	Published (VoR) - Sept 2021

Funding

Funding: This research was funded by the Deanship of Scientific Research at Taibah University, Saudi Arabia, project number (CSE—4). Acknowledgments: The authors would like to thank the Deanship of Scientific Research at Taibah University, Saudi Arabia, for funding this research project number (CSE—4).

Keywords

Convolution neural networks
Deep learning
LSTM
Pretrained model
Rumor detection
Twitter analysis
Word embedding

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10.3390/APP11177940

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title = "A novel hybrid deep learning model for detecting covid-19-related rumors on social media based on lstm and concatenated parallel cnns",

keywords = "Convolution neural networks, Deep learning, LSTM, Pretrained model, Rumor detection, Twitter analysis, Word embedding",

author = "Mohammed Al-Sarem and Abdullah Alsaeedi and Faisal Saeed and Wadii Boulila and Omair Ameerbakhsh",

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AU - Al-Sarem, Mohammed

AU - Alsaeedi, Abdullah

AU - Saeed, Faisal

AU - Boulila, Wadii

AU - Ameerbakhsh, Omair

PY - 2021/9

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KW - Convolution neural networks

KW - Deep learning

KW - LSTM

KW - Pretrained model

KW - Rumor detection

KW - Twitter analysis

KW - Word embedding

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VL - 11

JO - Applied Sciences (Switzerland)

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ER -

A novel hybrid deep learning model for detecting covid-19-related rumors on social media based on lstm and concatenated parallel cnns

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Keywords

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