hate-speech-and-offensive-language VS ThoughtSource

Compare hate-speech-and-offensive-language vs ThoughtSource and see what are their differences.

ThoughtSource

A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/ (by OpenBioLink)
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hate-speech-and-offensive-language ThoughtSource
2 1
779 899
- 1.9%
1.9 0.9
over 1 year ago 6 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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hate-speech-and-offensive-language

Posts with mentions or reviews of hate-speech-and-offensive-language. We have used some of these posts to build our list of alternatives and similar projects.
  • How to make a class column for a classifier from sentiment analysis results?
    1 project | /r/learnpython | 24 Jan 2022
    I've used NRCLex to perform sentiment analysis on some Twitter data. I have hate speech classifier code (https://github.com/t-davidson/hate-speech-and-offensive-language/blob/master/classifier/final_classifier.ipynb) I want to pass the dataset through, but before I can I need to have a "class" column for the model. For those not familiar, NRCLex returns scores for 10 emotions: anticipation, joy, anger, fear, surprise, disgust, positive, negative, sadness and trust. The table looks like this (letters denoting emotions):
  • Where do we go from here and who is going to step up to help us?
    1 project | news.ycombinator.com | 28 Jan 2021
    Some of this exists, and both Quora and Facebook (among others) use it extensively. Both hate speech and porn are good targets for machine learning. It needs supervision, but it can take a lot of load off human moderators.

    Open source implementations exist, e.g.:

    https://github.com/t-davidson/hate-speech-and-offensive-lang...

    I suspect more message board will want to start applying these sooner rather than later. Most have already figured out that they need anti-spam tools, rather than it coming as a surprise when they roll things out and it fills up with bots. The technology is similar.

    You mention being able to share that information across boards, and I don't know of any widespread implementation of that. You can, at least, let somebody else handle your authentication, which slightly slows their ability to create new accounts when you blacklist one. I'd like to see those sites distinguish "aged" accounts, so that it at least takes some effort or cost to use a new account.

ThoughtSource

Posts with mentions or reviews of ThoughtSource. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing hate-speech-and-offensive-language and ThoughtSource you can also consider the following projects:

hashformers - Hashformers is a framework for hashtag segmentation with Transformers and Large Language Models (LLMs).

medmcqa - A large-scale (194k), Multiple-Choice Question Answering (MCQA) dataset designed to address realworld medical entrance exam questions.

Tegridy-MIDI-Dataset - Tegridy MIDI Dataset for precise and effective Music AI models creation.

goodreads - code samples for the goodreads datasets

toxicity - The world's largest social media toxicity dataset.

PLOD-AbbreviationDetection - This repository contains the PLOD Dataset for Abbreviation Detection released with our LREC 2022 publication

cia - 🐱‍💻 CIA Factbook data analysis and dataset reconstruction, modification, and tuning go here.

datasets - 🎁 5,400,000+ Unsplash images made available for research and machine learning

ToolQA - ToolQA, a new dataset to evaluate the capabilities of LLMs in answering challenging questions with external tools. It offers two levels (easy/hard) across eight real-life scenarios.

airline-sentiment-streaming - Streaming with Airline Sentiment. Utilizing Cloudera Machine Learning, Apache NiFi, Apache Hue, Apache Impala, Apache Kudu

PIXIU - This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).

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