Tell Me Why It’s Fake: Developing an Explainable User Interface for a Fake News Detection System

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Presentation @ XAI.it 2022: 3rd Italian Workshop on Explainable Artificial Intelligence, co-located with AIxIA 2022, 30th November 2022, Udine, Italy.

Science

Tell Me Why It’s Fake:
Developing an Explainable User Interface for
a Fake News Detection System
Erasmo Purificato, Saijal Shahania, and Ernesto William De Luca

“
Disinformation or falsehoods presented as real
news or actual news that is claimed to be untrue.
Fake News definition by the American Dialect Society as 2017 “word of the year”

The need of fake news detection tools
◎ Advent and rapid diffusion of internet bots (Ferrara et al., 2016)
◎ 17% of Twitter accounts are suspected to be bots, contributing to 30% of the
number of tweets posted (Liu, 2019)
◎ 500 million tweets published every day (internetlivestats.com, 2021)

Manual fact-checking tool
(www.politifact.com/truth-o-meter/)

dEFEND(Shu et al., 2019)
Automatic explainable fact-checking tool

Logic architecture of the fake news detection system

Next steps
◎ Implementation of “What if…” functionality;
◎ Addition of new explainability methods;
◎ User study with domain experts to assess the effectiveness of the whole system.

Thanks!
I am Erasmo Purificato
You can find me at:
https://erasmopurif.com
@erasmopurif11
erasmo.purificato@ovgu.de

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Tell Me Why It’s Fake: Developing an Explainable User Interface for a Fake News Detection System

1. Tell Me Why It’s Fake: Developing an Explainable User Interface for a Fake News Detection System Erasmo Purificato, Saijal Shahania, and Ernesto William De Luca

2. The concept of Fake News

3. “ Disinformation or falsehoods presented as real news or actual news that is claimed to be untrue. Fake News definition by the American Dialect Society as 2017 “word of the year”

4. The need of fake news detection tools ◎ Advent and rapid diffusion of internet bots (Ferrara et al., 2016) ◎ 17% of Twitter accounts are suspected to be bots, contributing to 30% of the number of tweets posted (Liu, 2019) ◎ 500 million tweets published every day (internetlivestats.com, 2021)

5. Manual fact-checking tool (www.politifact.com/truth-o-meter/)

6. dEFEND(Shu et al., 2019) Automatic explainable fact-checking tool

7. Logic architecture of the fake news detection system

8. Input methods

9. Explainable User Interface

10. Explainable User Interface

11. Explainable User Interface

12. Explainable User Interface

13. Explainer Dashboard

14. Next steps ◎ Implementation of “What if…” functionality; ◎ Addition of new explainability methods; ◎ User study with domain experts to assess the effectiveness of the whole system.

15. Thanks! I am Erasmo Purificato You can find me at: https://erasmopurif.com @erasmopurif11 erasmo.purificato@ovgu.de

Tell Me Why It’s Fake: Developing an Explainable User Interface for a Fake News Detection System

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