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Exploring ML for building a more robust and scalable version of Kindly #57
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@nathanfletcher: can you document here some of the findings? Thanks! 🙏 |
I will start here with the basics from discussions with @nathanbaleeta A number of things I'll be looking into:
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PROBLEM DEFINITION Twitter is an American microblogging and social networking service on which users post and interact with messages known as "tweets". Registered users can post, like, and retweet tweets, but unregistered users can only read them. (Wikipedia) Cyberbullying is the use of information and communication technology to harass and harm in a deliberate, repetitive, and hostile manner. Types of cyberbullying include bullying someone through social media, harassment, sexting, cyberstalking, deception, impersonation, and sending nasty messages via chat rooms and instant messenger. Here are more examples of cyberbulling. According to Twitter demographics published by www.statista.com as of April 2021: users aged less than 24 years old were almost the 24 percent worldwide as shown below in the graphic: SOLUTION |
@lacabra This repository is where my files and practical learnings are https://github.com/nathanfletcher/ml_text_classification |
@nathanfletcher to include this in documentation before closing it. |
Looking into ways to achieve what Kindly #41 does to make it better.
This may also result in solutions that are not vendor-locked.
Maybe @nathanbaleeta may have a few ideas.
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