most citedBotShape: A Novel Social Bots Detection Approach via Behavioral Patterns

28 citations · 31 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SI2023

FakeSwarm: Improving Fake News Detection with Swarming Characteristics

Jun Wu, Xuesong Ye

The proliferation of fake news poses a serious threat to society, as it can misinform and manipulate the public, erode trust in institutions, and undermine democratic processes. To…

cs.AI20232 cited

BotTriNet: A Unified and Efficient Embedding for Social Bots Detection via Metric Learning

Jun Wu, Xuesong Ye, Yanyuet Man

The rapid and accurate identification of bot accounts in online social networks is an ongoing challenge. In this paper, we propose BOTTRINET, a unified embedding framework that lev…

cs.AI20231 cited

FineEHR: Refine Clinical Note Representations to Improve Mortality Prediction

Jun Wu, Xuesong Ye, Chengjie Mou +1

Monitoring the health status of patients in the Intensive Care Unit (ICU) is a critical aspect of providing superior care and treatment. The availability of large-scale electronic…

cs.LG2023

MedLens: Improve Mortality Prediction Via Medical Signs Selecting and Regression

Xuesong Ye, Jun Wu, Chengjie Mou +1

Monitoring the health status of patients and predicting mortality in advance is vital for providing patients with timely care and treatment. Massive medical signs in electronic hea…

cs.SI202328 cited

BotShape: A Novel Social Bots Detection Approach via Behavioral Patterns

Jun Wu, Xuesong Ye, Chengjie Mou

An essential topic in online social network security is how to accurately detect bot accounts and relieve their harmful impacts (e.g., misinformation, rumor, and spam) on genuine u…