Skip to main content

Identifying toxic text from a Google Chrome Extension

  • Chapter
  • First Online:
Practical TensorFlow.js
  • 830 Accesses

Abstract

Online toxicity is an unfortunate, challenging, and unwanted reality of the Internet. Take a stroll down any online comment section, Twitter thread, or multiplayer game, and you will find a piece of obscene and offensive text that will make you say "wow." In those circumstances, there is not much we can do, except for clicking the "report" button and hoping that someone or some magic entity identifies and removes the comment. This chapter addresses this issue. Here, we will build a tool capable of detecting and classifying toxic content.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://github.com/tensorflow/tfjs-models/tree/master/universal-sentence-encoder

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Juan De Dios Santos Rivera

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Rivera, J.D.D.S. (2020). Identifying toxic text from a Google Chrome Extension. In: Practical TensorFlow.js. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-6273-3_6

Download citation

Publish with us

Policies and ethics