EnsMulHateCyb: Multilingual hate speech and cyberbully detection in online social media
Nowadays, users across the globe interact with one another for information exchange,
communication, and association on various online social media. However, some individuals …
communication, and association on various online social media. However, some individuals …
Fuser: An enhanced multimodal fusion framework with congruent reinforced perceptron for hateful memes detection
F Wu, B Gao, X Pan, L Li, Y Ma, S Liu, Z Liu - Information Processing & …, 2024 - Elsevier
As a multimodal form of hate speech on social media, hateful memes are more aggressive
and cryptic threats to the real life of humans. Automatic detection of hateful memes is crucial …
and cryptic threats to the real life of humans. Automatic detection of hateful memes is crucial …
The impact factors of social media users' forwarding behavior of COVID-19 vaccine topic: based on empirical analysis of Chinese Weibo users
K Sun, H Wang, J Zhang - Frontiers in Public Health, 2022 - frontiersin.org
Introduction Social media, an essential source of public access to information regarding the
COVID-19 vaccines, has a significant effect on the transmission of information regarding the …
COVID-19 vaccines, has a significant effect on the transmission of information regarding the …
Measuring social support for depression on social media: A multifaceted study on user interaction and emotional spread
XK Wu, YY Zhou, B Zhong - Telematics and Informatics, 2024 - Elsevier
User interaction within social media groups is increasingly vital for offering social support to
individuals experiencing mental health issues. However, measuring social support in these …
individuals experiencing mental health issues. However, measuring social support in these …
Unveiling evolving nationalistic discourses on social media: a cross-year analysis in pandemic
The global pandemic has dramatically reshaped public discourse, with social media
emerging as a pivotal platform for these discussions. This study delves into evolving …
emerging as a pivotal platform for these discussions. This study delves into evolving …
Mining Multiplatform Opinions During Public Health Crisis: A Comparative Study
Emerging infectious diseases pose a growing threat to human society and have sparked
extensive public discussions on social media. Although numerous efforts have been made …
extensive public discussions on social media. Although numerous efforts have been made …
Data-Driven Regression Modeling for Measuring the Influence of Infodemic over Social Media
TF Zhao, LL Zhang, ZX Zhang… - 2023 5th International …, 2023 - ieeexplore.ieee.org
The infodemic, which encompasses rumors, fake news, disinformation, and misinformation,
has resulted in significant collateral damage alongside epidemics. However, the main …
has resulted in significant collateral damage alongside epidemics. However, the main …
Artificial intelligence inspired method for cross-lingual cyberhate detection from low resource languages
M Kaur, M Saini - ACM Transactions on Asian and Low-Resource …, 2024 - dl.acm.org
The appearance of inflammatory language on social media by college or university students
is quite prevalent, inspiring platforms to engage in community safety mechanisms …
is quite prevalent, inspiring platforms to engage in community safety mechanisms …
Selling hope versus hate: the impact of partisan social media messaging on social distancing during the COVID-19 pandemic
Purpose This study aims to examine the role of hope and hate in political leaders' messages
in influencing liberals versus conservatives' social-distancing behavior during the COVID-19 …
in influencing liberals versus conservatives' social-distancing behavior during the COVID-19 …
[HTML][HTML] FDNet: Focal Decomposed Network for efficient, robust and practical time series forecasting
L Shen, Y Wei, Y Wang, H Qiu - Knowledge-Based Systems, 2023 - Elsevier
This paper presents FDNet: a Focal Decomposed Network for efficient, robust and practical
time series forecasting. We break away from conventional deep time series forecasting …
time series forecasting. We break away from conventional deep time series forecasting …