1/Excited to collaborate with @rmichaelalvarez at @Caltech on #MeToo
movement on @Twitter with Maya Srikant, Nicholas Adams-Cohen @anqi_liu33 Online #trolls affect women + minorities disproportionately. Personally been a victim to #trolls from sexualized messages to gun threatshttps://twitter.com/arXiv_Daily/status/1194965793059917824 …
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2/We use word embeddings
#NLP to detect new keywords for rapidly evolving conversations. We also contrast how starkly word embeddings change based on data used.#MeToo
vs #reddit#redpill @rmunro_rob@VioletNPeng have also shown gender bias in#NLP modelspic.twitter.com/gxklfzgskT
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4/
@JCornebise has shown how#trolls target#women politicians more disproportionately.@Twitter and other social media need to figure out how to create a better experience for women and minorities online1 reply 3 retweets 11 likesShow this thread -
Replying to @AnimaAnandkumar @rmichaelalvarez and
Thought you might be interested at our 2018 work.. https://arxiv.org/pdf/1803.08022.pdf …
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Replying to @maidylm @rmichaelalvarez and
Thank you! We will look at it closely
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Replying to @AnimaAnandkumar @rmichaelalvarez and
I wish we could've done a better job.. but hope its useful for your research.. Please let me know if you need any other info.. happy to help
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I see that it is closely related. We used word embeddings instead of topic modeling, but I can see both can be useful. We will make sure to cite your work in revised version
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Replying to @AnimaAnandkumar @rmichaelalvarez and
Most definitely.. This is a very important topic especially how much it affects emotional and physical well-being. I cannot imagine what you have gone through personally. I am so sorry.
0 replies 0 retweets 1 likeThanks. Twitter will use this to make your timeline better. UndoUndo
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