Margaret's class project sadly doesn't have a title, yet. BUT! It can be found here.
I thought that what you found about the number of retweets and favorites for cats and dogs was interesting. It seems kind of strange that cat posts are more likely to be retweeted, and dog posts are more likely to be favorites. Some of the time zones that came up were also interesting (Abu Dhabi, Tunis, Caracas, etc.). I think that looking more into the different neologisms could be interesting. If it's possible to get tweets that are about dogs or cats, you could maybe try looking into how often words like "doggo" and "kitteh" are used in these posts. You could also use time zones/locations to see if these words are used more frequently in certain regions.
- I think your project is really interesting and the way you have it laid out right now makes it easy to follow
- I also think that it's great that you're expanding on the tweepy practice we did in class! I would have loved to have had more time to delve into it and I can't wait to see what other results you get!
- It's really interesting that cats get retweeted much more than dogs do despite being posted much less often
- One thought from me is that under the neologisms you might want to also include things like 'kitty', 'doggy', 'kitten', or 'puppy'
- If there's time, you might also want to try adding adjectives to the hashtags like FunnyCat or something like that. I feel like a lot of cat pictures or videos that are funny cat videos
- Please update the README
- I like the exploded view pie charts!
- Nice work with tweepy!
- Is it possible that this data can change throughout the day?
- Since you're making a search and only taking 1000 of the most recent items, it might be interesting to re-run this at different points. Or, you could scrape much larger dataset and work with that.
- I'm an old man so I had no idea about 'toebeans'!
- Nice use of plots and tweepy - I need to add visualizations
- I was surprised by differences between retweets and likes in terms of numbers and also how they differed between cats and dogs
- Although the results look significant, perhaps you could so some simple statistical analyses to confirm your findings, for example Chi Square (which I believe is part of math module)
- You have really awesome visualizations working for your data, and it's cool that your actively pulling the latest data from Twitter so your data is not static
- Perhaps maybe there can be some way to automate the downloading of data from Twitter to get equal samples of tweets from different areas throughout the day? It looks like its being done manually at the moment so including automation could be interesting!!
- kitteh and toe bean are tags for cats! I learned a lot from your project about people's posts about cats and dogs - I'd never thought to compare these!
- This project idea is interesting! I've heard of doggo and doge, but I've never heard of kitteh or toe beans.
- You're doing some really cool analyses!
- I was not surprised to see that dogs were mentioned more than cats, but I was really surprised that the number of retweets for cats was so much higher.
- That said, later in the analysis, it sounds like dogs are retweated more and cats favorited more? Was this because you removed NULL time zones?
- How do you intend to compare these different numbers of mean rt. and mean fav? What do you think it means that there is such a difference when you take out NULL value time zones?
- The summary markdown cells for cats and dogs were very helpful!!