1) The document discusses tools for supporting rumour verification, including classifying rumours by stance and determining rumour veracity. 2) It describes using a four-class system (SDQC) to classify rumours by stance and notes challenges in classifying minority classes. 3) Contact information is provided for the project coordinators and partners developing rumour verification and stance classification tools and services.

1. TOOLS FOR SUPPORTING RUMOUR VERIFICATION
Carolina Scarton (University of Sheffield)
@carolscarton
MAISoN
online conference, 19/10/2020

2. Rumours
2
"an unofficial interesting story or piece of news that might be
true or invented, and quickly spreads from person to person"
(Cambridge dictionary)

3. Verifying Rumours and Analysing Conversational Threads
3
https://twitter.com/emmanuelmacron/status/1164617008962527232

4. Verifying Rumours: Demo Example
4

5. Verifying Rumours and Analysing Conversational Threads (1)
5

6. Verifying Rumours and Analysing Conversational Threads (2)
6

7. Rumour Stance Classification
➢ Four-class classification: SDQC
➢ Very imbalanced problem (RumourEval data stats)
➢ Systems do not perform well for minority classes

8. Rumour Stance Classification

9. Rumour Stance Classification
Further improvements for deny when using Bi-LSTM over the
average of the last 4 BERT hidden layers

10. Rumour Veracity and Stance as a Service
10
https://cloud.gate.ac.uk

11. Project Contacts
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• Dr. Milena Yankova-Doseva
Project Coordinator, Ontotext AD
email:milena.yankova@ontotext.com
• Zlatina Marinova
Administrative Coordinator, Ontotext AD
email: zlatina.marinova@ontotext.com
• Prof. Kalina Bontcheva
Scientific Director, University of Sheffield
email: k.bontcheva@sheffield.ac.uk
•
• Nikos Sarris
Exploitation Director, ATC
email: n.sarris@atc.gr
• Denis Teyssou
Innovation Manager, AFP
email: denis.teyssou@afp.com
• Jochen Spangenberg
Dissemination Lead, DW
email: jochen.spangenberg@dw.com
•

12. THANK YOU FOR YOUR ATTENTION!
www.weverify.eu
@WeVerify