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Description

Checkwise meticulously assesses factual statements and delivers a conclusion supported by the specific sources it utilized, instead of relying on an ambiguous confidence score. Users can submit claims in various formats, including plain text, article URLs, or even live video checks while playback occurs. During each verification, Checkwise actively seeks out evidence, examines the discovered pages, and presents a verdict for each source along with the relevant supporting excerpts. Each source is assigned a reliability rating ranging from A to D, determined prior to the check based on factors such as editorial standards, correction policies, transparency regarding ownership and funding, and overall reputation. The criteria used for this grading system are openly shared, and each evaluated site features a public page that elucidates its score, allowing the editorial team to understand the rationale behind a verdict and challenge a rating if needed. Accessible as a web application, Checkwise also offers a browser extension compatible with Chrome, Firefox, Edge, and Brave, along with a REST API designed for teams to incorporate checks into their own editorial or moderation workflows. This comprehensive approach ensures that users have a clear understanding of the verification process and the reliability of the sources being evaluated.

Description

ClaimBuster serves as the overarching platform for all fact-checking initiatives within the IDIR Lab. Originally launched to develop an AI system capable of identifying claims that warrant verification, it has progressively advanced towards achieving the ideal of fully automated fact-checking. While journalists primarily utilize ClaimBuster, it is designed for anyone motivated to confront misinformation. Accessing our models is straightforward through our API, which only requires the registration of a free API key. The success of ClaimBuster relies heavily on the contributions from individuals who label data. We encourage you to create an account and participate in labeling to enhance our model's effectiveness. Additionally, we've made our machine learning model training code available as open-source, inviting skilled AI engineers to contribute their expertise. Our claim-detection model even retweets posts it identifies as potentially needing fact-checking, expanding its utility in real-time. By participating, you can play an essential role in the ongoing battle against misinformation.

API Access

Has API

API Access

Has API

Screenshots View All

No images available

Screenshots View All

Integrations

GitHub
Google Colab
X (Twitter)

Integrations

GitHub
Google Colab
X (Twitter)

Pricing Details

$15/month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Checkwise

Country

Switzerland

Website

checkwise.ai

Vendor Details

Company Name

ClaimBuster

Founded

2015

Country

United States

Website

idir.uta.edu/claimbuster/

Product Features

Product Features

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