hate-speech-and-offensive-language VS PLOD-AbbreviationDetection

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

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hate-speech-and-offensive-language PLOD-AbbreviationDetection
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over 1 year ago about 2 years ago
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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.

PLOD-AbbreviationDetection

Posts with mentions or reviews of PLOD-AbbreviationDetection. We have used some of these posts to build our list of alternatives and similar projects.
  • Clustering to find abbreviations
    1 project | /r/LanguageTechnology | 1 Jun 2022
    Finally, the main problem with unsupervised learning is that you won't be able to reliably measure system performance or improvement. In my view, any time you can spend annotating and collecting data for a (semi-)supervised solution will be well-spent. Existing datasets can also get you started with model development, such as https://github.com/surrey-nlp/PLOD-AbbreviationDetection. Once you have a good model on a conventional dataset, you should be able to start generalizing it to your specific task/dataset.

What are some alternatives?

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

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

nlp - Repository for all things Natural Language Processing

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

converse - Conversational text Analysis using various NLP techniques

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

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/

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

transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

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

100daysofpractice-dataset - Data from Instagram posts with the hashtag #100daysofpractice.

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