OLTW-TEC: online learning with sliding windows for text classifier ensembles.

ABSTRACT: In the digital age, rapid dissemination of information has elevated the challenge of distinguishing between authentic news and disinformation. This challenge is particularly acute in regions experiencing geopolitical tensions, where information plays a pivotal role in shaping public perception and policy. The prevalence of disinformation in the Ukrainian-language information space, intensified by the hybrid war with russia, necessitates the development of sophisticated tools for its detection and mitigation. Our study introduces the "Online Learning with Sliding Windows for Text Classifier Ensembles" (OLTW-TEC) method, designed to address this urgent need. This research aims to develop and validate an advanced machine learning method capable of dynamically adapting to evolving disinformati

SUBMITTER: Lipianina-Honcharenko K 

PROVIDER: S-EPMC11422347 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature