activity
20162022
most citedAnalyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media

8 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2022

Probing Cross-modal Semantics Alignment Capability from the Textual Perspective

Zheng Ma, Shi Zong, Mianzhi Pan +4

In recent years, vision and language pre-training (VLP) models have advanced the state-of-the-art results in a variety of cross-modal downstream tasks. Aligning cross-modal semanti…

cs.CL2022

Analyzing the Intensity of Complaints on Social Media

Ming Fang, Shi Zong, Jing Li +3

Complaining is a speech act that expresses a negative inconsistency between reality and human expectations. While prior studies mostly focus on identifying the existence or the typ…

cs.CL2022

Doctor Recommendation in Online Health Forums via Expertise Learning

Xiaoxin Lu, Yubo Zhang, Jing Li +1

Huge volumes of patient queries are daily generated on online health forums, rendering manual doctor allocation a labor-intensive task. To better help patients, this paper studies…

cs.CL2020

Measuring Forecasting Skill from Text

Shi Zong, Alan Ritter, Eduard Hovy

People vary in their ability to make accurate predictions about the future. Prior studies have shown that some individuals can predict the outcome of future events with consistentl…

cs.CL20198 cited

Analyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media

Shi Zong, Alan Ritter, Graham Mueller +1

Breaking cybersecurity events are shared across a range of websites, including security blogs (FireEye, Kaspersky, etc.), in addition to social media platforms such as Facebook and…

cs.LG2016

Cascading Bandits for Large-Scale Recommendation Problems

Shi Zong, Hao Ni, Kenny Sung +3

Most recommender systems recommend a list of items. The user examines the list, from the first item to the last, and often chooses the first attractive item and does not examine th…