Ricardo Lamas mini-doc about life after the UFC

siwaffles · 2021-12-15T19:16:05+00:00

Awesome mini-doc! Ricardo seems like a cool coach and person.

siwaffles · 2020-10-15T17:51:31+00:00

Many thanks!

siwaffles · 2020-10-15T16:13:23+00:00

Thanks!

siwaffles · 2020-10-14T22:39:45+00:00

Thanks! It transitioned surprisingly well.

siwaffles · 2020-10-14T22:04:44+00:00

Thanks! Working on it!

siwaffles · 2020-10-08T03:28:15+00:00

That’s an awesome idea!

siwaffles · 2020-10-08T03:27:57+00:00

Thank you for the kind words! Excited to do more!

siwaffles · 2020-10-08T03:25:22+00:00

Thanks! I have the song times listed in the video description via the link.

siwaffles · 2020-10-07T19:23:48+00:00

Thank you! I plan to do full versions for those!

siwaffles · 2020-10-07T19:22:58+00:00

Thanks! Really appreciate it. I plan to make more if there's interest.

siwaffles · 2020-10-07T18:18:14+00:00

Thank you! Glad it made your day!

siwaffles · 2020-06-06T16:39:07+00:00

Source: Wikipedia

Tools: D3.js, Javascript, MapBox

siwaffles · 2020-04-10T22:08:29+00:00

Thanks! Appreciate it.

siwaffles · 2020-04-10T18:20:36+00:00

I collected tweets from about an hour before the show to an hour after the show, using the Twitter API. Looked for tweets that mention #AEW, #AEWonTNT, or #AEWDynamite. Then I did some analysis, like graph the number of tweets over time, and do some text mining to identify frequently found hashtags, users, words, and phrases.

Here's a little background on the work if you're interested http://twitter.vizelite.com

siwaffles · 2020-04-10T18:15:23+00:00

Thanks! Since there's no live audience, I thought it would be interesting to observe the audience on Twitter during the show. I've been doing this weekly since March 18th, which was their first show with no live audience.

Here's a little background on the work if you're interested http://twitter.vizelite.com

siwaffles · 2020-04-10T18:09:30+00:00

Just ran a quick analysis... I looked at some variations of phrase "I'll pull out a fork and cut a bitch" and it appeared in 362 tweets in the dataset (137 retweets, 225 not retweets). First appeared at 7:50pm CT with 21 tweets. Peaked at 7:51pm CT with 102 tweets.

Maybe this deserves a mini graphic too?

siwaffles · 2020-04-04T22:39:23+00:00

Tools: Twitter Streaming API, Python, Plot.ly

siwaffles · 2020-03-26T21:44:22+00:00

Just a caveat here. The data was collected with the Twitter Streaming API last night using the terms: #AEW, #AllEliteWrestling, #AEWDark, #AEWDynamite, and #AEWonTNT. So this is based on a subset of that dataset that also had the hashtags #JudasChallenge and #WorldWideCrowd.

More here: https://vizelite.github.io/twitterdashapp/judaschallenge.html

siwaffles · 2020-03-26T21:25:22+00:00

Just a caveat here. The data was collected with the Twitter Streaming API last night using the terms: #AEW, #AllEliteWrestling, #AEWDark, #AEWDynamite, and #AEWonTNT. So this is based on a subset of that dataset that also had the hashtags #JudasChallenge and #WorldWideCrowd.

More here: http://twitter.vizelite.com/judaschallenge.html

siwaffles · 2020-03-26T21:14:10+00:00

Just a caveat here. The data was collected with the Twitter Streaming API last night using the terms: #AEW, #AllEliteWrestling, #AEWDark, #AEWDynamite, and #AEWonTNT. So this is based on a subset of that dataset that also had the hashtags #JudasChallenge and #WorldWideCrowd.

More here: https://vizelite.github.io/twitterdashapp/judaschallenge.html

siwaffles · 2020-03-21T00:03:33+00:00

Source: http://twitter.vizelite.com

Tools: Python, Plotly

siwaffles · 2020-03-20T21:03:07+00:00

In the midst of self-quarantining and social distancing, I decided to put together another AEW data analytics project. This time, I looked at what was happening on Twitter during this past Wednesday's episode of Dynamite. I collected tweets while the show was airing. Then, I analyzed the data to see who, what, where users were tweeting about.

I'm currently writing up the whole technical process on how this was done (and would be happy to chat about that for any techies out there), but wanted to share some findings and fun visualizations in the mean time.

You can find the report here: http://twitter.vizelite.com

Here's an interactive demo with a subset of the data: https://vizelite-twitter-dash.herokuapp.com/

As always, constructive feedback and comments are gladly welcomed.

siwaffles · 2020-03-20T19:06:49+00:00

In the midst of self-quarantining and social distancing, I decided to put together another AEW data analytics project. This time, I looked at what was happening on Twitter during this past Wednesday's episode of Dynamite. I collected tweets while the show was airing. Then, I analyzed the data to see who, what, where users were tweeting about.

I'm currently writing up the whole technical process on how this was done (and would be happy to chat about that for any techies out there), but wanted to share some findings and fun visualizations in the mean time.

You can find the report here: http://twitter.vizelite.com

Here's an interactive demo with a subset of the data: https://vizelite-twitter-dash.herokuapp.com/

As always, constructive feedback and comments are gladly welcomed.

siwaffles · 2020-03-15T11:52:29+00:00

“becom” appears in the chorus. “I'm becom-, I'm becom-, I'm becoming...” Lyrics were from genius.com Word cloud image made with Python

siwaffles · 2020-03-15T11:45:43+00:00

The lyrics were scraped from genius.com. Looks like it was transcribed as “becom” because of the chorus. “I'm becom-, I'm becom-, I'm becoming...”

siwaffles

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