Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media

by   Yizhou Zhang, et al.

Recent years have witnessed the rise of misinformation campaigns that spread specific narratives on social media to manipulate public opinions on different areas, such as politics and healthcare. Consequently, an effective and efficient automatic methodology to estimate the influence of the misinformation on user beliefs and activities is needed. However, existing works on misinformation impact estimation either rely on small-scale psychological experiments or can only discover the correlation between user behaviour and misinformation. To address these issues, in this paper, we build up a causal framework that model the causal effect of misinformation from the perspective of temporal point process. To adapt the large-scale data, we design an efficient yet precise way to estimate the Individual Treatment Effect(ITE) via neural temporal point process and gaussian mixture models. Extensive experiments on synthetic dataset verify the effectiveness and efficiency of our model. We further apply our model on a real-world dataset of social media posts and engagements about COVID-19 vaccines. The experimental results indicate that our model recognized identifiable causal effect of misinformation that hurts people's subjective emotions toward the vaccines.


page 1

page 2

page 3

page 4


VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media

Recent years have witnessed an increasing use of coordinated accounts on...

WeSeer: Visual Analysis for Better Information Cascade Prediction of WeChat Articles

Social media, such as Facebook and WeChat, empowers millions of users to...

CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts

Research community has witnessed substantial growth in the detection of ...

"Double vaccinated, 5G boosted!": Learning Attitudes towards COVID-19 Vaccination from Social Media

To address the vaccine hesitancy which impairs the efforts of the COVID-...

Opinion mining from twitter data using evolutionary multinomial mixture models

Image of an entity can be defined as a structured and dynamic representa...

Estimating Causal Effects of Tone in Online Debates

Statistical methods applied to social media posts shed light on the dyna...

Please sign up or login with your details

Forgot password? Click here to reset