and one with the start times all aligned. These are both lacking ID data, but interesting to see variety. x=time, y=tweetcount up to 100.pic.twitter.com/dFB2dVdulv
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and one with the start times all aligned. These are both lacking ID data, but interesting to see variety. x=time, y=tweetcount up to 100.pic.twitter.com/dFB2dVdulv
What are you hoping to learn from these visualizations?
Nothing, I’m just provoking visualization for fun
What about some cross between a histogram and heatmap to show changes in tempo of tweeting throughout the thread? Or the velocity/acceleration of tweets over time? I think themes for each thread would be interesting too but not just a word cloud.
themes are probably really hard to tease out 
Something like TF-IDF would be a good starting place for each thread. Finding similarities and differences from threads (and the seed topic) could be interesting. I would be interested to see which threads are more similar/different across topics.
Each thread? Wouldn’t that be a natural fit for the whole palooza to detect top *shared* themes?
Could do topic models based on the entire corpus of the threads, but there might not be enough tweets to create a decent model
Yeah 100x100=10k tweets = ~100k words... I’d guess min is a million words
The people doing the threads are probably more deliberate about their language though. Even presence and frequency would probably be valuable. Probably worth a quick experiment. I might have time to put this through some basic NLP tools in the next few days.
Go for it,should be fun and i suspect the thread authors would get a kick out of seeing themselves in a tf-idf mirror
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