公开(公告)号：US20230019410A1

公开(公告)日：2023-01-19

申请号：US17865963

申请日：2022-07-15

Applicant: Qatar Foundation for Education, Science and Community Development

Inventor： Preslav I. Nakov ,  Panayot Panayotov ,  Utsav Shukla ,  Husrev Taha Sencar

IPC: G06F16/906 ,  G06F16/907 ,  G06N3/02 ,  G06K9/62

Abstract: The present disclosure provides new and innovative systems and methods for profiling bias for data sources, specifically publishers of news articles. A variety of embodiments include a computer-implemented method for profiling a data source includes obtaining an indication of a first data source, determining visitor and keyword data for the first data source, determining metadata for the first data source, generating a source similarity graph for the first data source, the source similarity graph indicating at least one similar data source and, for each similar data source, a bias score for the similar data source, classifying the first data source based on the bias scores for the at least one similar data source, generating a notification indicating the first data source and the classification of the first data source, and providing the notification.

公开(公告)号：US20230004712A1

公开(公告)日：2023-01-05

申请号：US17855248

申请日：2022-06-30

Applicant: Qatar Foundation for Education, Science and Community Development ,  Massachusetts Institute of Technology

Inventor： Preslav I. Nakov ,  Giovanni Da San Martino ,  Seunghak Yu

IPC: G06F40/205 ,  G06F40/289 ,  G06F3/04842

Abstract: Explainable propaganda detection is provided by parsing each sentence of a plurality of sentences in an article for structural details; identifying, via a machine learning model, dimensional features across the plurality of sentences based on the structural details; identifying, via the machine learning model, a propagandizing tactic demonstrated in each sentence of the plurality of sentences based a covariance score to the propagandizing tactic and the plurality of dimensional features identified for a given sentence; and displaying, in a user interface that includes the article, propaganda labels corresponding to the propagandizing tactic identified for each sentence of the plurality of sentences.

公开(公告)号：US12223265B2

公开(公告)日：2025-02-11

申请号：US17855248

申请日：2022-06-30

Applicant: Qatar Foundation for Education, Science and Community Development ,  Massachusetts Institute of Technology

Inventor： Preslav I. Nakov ,  Giovanni Da San Martino ,  Seunghak Yu

IPC: G06F40/205 ,  G06F3/04842 ,  G06F40/289

Abstract: Explainable propaganda detection is provided by parsing each sentence of a plurality of sentences in an article for structural details; identifying, via a machine learning model, dimensional features across the plurality of sentences based on the structural details; identifying, via the machine learning model, a propagandizing tactic demonstrated in each sentence of the plurality of sentences based a covariance score to the propagandizing tactic and the plurality of dimensional features identified for a given sentence; and displaying, in a user interface that includes the article, propaganda labels corresponding to the propagandizing tactic identified for each sentence of the plurality of sentences.

公开(公告)号：US20230036352A1

公开(公告)日：2023-02-02

申请号：US17871206

申请日：2022-07-22

Applicant: Qatar Foundation for Education, Science and Community Development

Inventor： Preslav I. Nakov ,  Momchil Hardalov ,  Isabelle Augenstein ,  Arnav Arora

IPC: G06F40/284 ,  G06F40/205 ,  G06N3/08

Abstract: Cross-domain label-adaptive stance detection is provided by receiving a natural language input; tokenizing the natural language input by a shared tokenizer to identify tokens in the natural language input; parsing the tokens by a plurality of domain expert encoder blocks to produce a corresponding plurality of domain encodings for the natural language input; parsing the tokens by a global encoder block to produce a global encoding for the natural language input; processing the plurality of domain encodings and the global encoding by a label embedding layer to produce a probability distribution for a stance of the natural language input; and outputting the stance for the natural language input.