3 citations · 9 across the 6 of their papers we have counts for
8 papers
Unsupervised Domain-agnostic Fake News Detection using Multi-modal Weak Signals
Amila Silva, Ling Luo, Shanika Karunasekera +1
The emergence of social media as one of the main platforms for people to access news has enabled the wide dissemination of fake news. This has motivated numerous studies on automat…
Knowledge Enhanced Multi-modal Fake News Detection
Yi Han, Amila Silva, Ling Luo +2
Recent years have witnessed the significant damage caused by various types of fake news. Although considerable effort has been applied to address this issue and much progress has b…
Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Data
Amila Silva, Ling Luo, Shanika Karunasekera +1
With the rapid evolution of social media, fake news has become a significant social problem, which cannot be addressed in a timely manner using manual investigation. This has motiv…
METEOR: Learning Memory and Time Efficient Representations from Multi-modal Data Streams
Amila Silva, Shanika Karunasekera, Christopher Leckie +1
Many learning tasks involve multi-modal data streams, where continuous data from different modes convey a comprehensive description about objects. A major challenge in this context…
On Predicting Personal Values of Social Media Users using Community-Specific Language Features and Personal Value Correlation
Amila Silva, Pei-Chi Lo, Ee-Peng Lim
Personal values have significant influence on individuals' behaviors, preferences, and decision making. It is therefore not a surprise that personal values of a person could influe…
OMBA: User-Guided Product Representations for Online Market Basket Analysis
Amila Silva, Ling Luo, Shanika Karunasekera +1
Market Basket Analysis (MBA) is a popular technique to identify associations between products, which is crucial for business decision making. Previous studies typically adopt conve…