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This is a binary classification model fine-tuned using the model 'bert-base-uncased'. It is built using a large Twitter dataset and is suitable especially for Twitter style data.

This can be used to classify the text into the categories of 'Privacy & Security' or 'Non-Privacy and Security'.

It achieved the following results on the evaluation set:

The validation scores for the module were as follows

Accuracy = 0.92

Class Precision Recall F1-Score
PrivSec(0) 0.91 0.94 0.92
Non-PrivSec(1) 0.93 0.89 0.91

Paper: The paper detailing how it was designed can be found here Perspectives of non-expert users on cyber security and privacy: An analysis of online discussions on twitter

Please cite the paper if you use this model :

Nandita Pattnaik, Shujun Li, and Jason R.C. Nurse. 2023.
Perspectives of non-expert users on cyber security and privacy: An analysis of online discussions on Twitter.
Computers & Security 125 (2023), 103008. https://doi.org/10.1016/j.cose.2022.103008

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