Friday, 28 August 2020
New algorithm can identify misogyny on Twitter
Researchers from the Queensland University of Technology (QUT) in Australia have developed an algorithm that detects misogynistic content on Twitter. The team developed the system by first mining 1 million tweets. They then refined the dataset by searching the posts for three abusive keywords: whore, slut, and rape. Next, they categorized the remaining 5,000 tweets as either misogynistic or not, based on their context and intent. These labeled tweets were then fed to a machine learning classifier, which used the samples to create its own classification model. The system uses a deep learning algorithm to adjust its knowledge of terminology as language evolves. While…
This story continues at The Next Web
Or just read more coverage about: Twitter
from Social Media – The Next Web https://ift.tt/3b2wuE0
via IFTTT
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment