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researcher

Jie Gao

Department of Computer Science

3 papers hereh-index 313.2k citations195 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.SI1
affiliations
  • Department of Computer Science
  • University of Sheffield
Homepage
same name
  • Jie Gao — 22 papers, h 36
  • Jie Gao — 20 papers, h 16
  • Jie Gao — 19 papers, h 24
  • Jie Gao — 16 papers, h 40
  • Jie Gao — 8 papers, h 8
  • Jie Gao — 8 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192023
most citedRP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media

22 citations · 39 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CL2023★ 1 cited

Logically at Factify 2: A Multi-Modal Fact Checking System Based on Evidence Retrieval techniques and Transformer Encoder Architecture

Pim Jordi Verschuuren, Jie Gao, Adelize van Eeden +2

In this paper, we present the Logically submissions to De-Factify 2 challenge (DE-FACTIFY 2023) on the task 1 of Multi-Modal Fact Checking. We describes our submissions to this cha…

cs.SI2020★ 22 cited

RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media

Jie Gao, Sooji Han, Xingyi Song +1

Early rumor detection (ERD) on social media platform is very challenging when limited, incomplete and noisy information is available. Most of the existing methods have largely work…

cs.CL2019★ 16 cited

Neural Language Model Based Training Data Augmentation for Weakly Supervised Early Rumor Detection

Sooji Han, Jie Gao, Fabio Ciravegna

The scarcity and class imbalance of training data are known issues in current rumor detection tasks. We propose a straight-forward and general-purpose data augmentation technique w…

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