Mertay Dayanc

Computer science

Hometown: Ankara, Incek, Turkey

Graduation date: Fall 2021

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FURI | Spring 2021

Understanding Machine vs Human Generated Text in News Articles

The aim of this research is to create a model that can take a text input to classify the content of the message into two categories, Machine Generated and Human Written. This research uses Hierarchical Attention Networks (HAN) trained with PolitiFact data to create the predictive model. This model can be run by websites for helping prevent disinformation. In the future, HAN can be trained to infer not only from words and sentences but also from the paragraphs, which can potentially provide more insight.

Mentor:

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Additional projects from this student

Real Time Multimodal Classification for Social Media Notifications

Designing a model that can take either an image, text or both will help classify social media message into different categories in real time.

Mentor:

  • FURI
  • Summer 2020