Author describes a lot of features with words, but would have really been great if they added some images of what they are describing for better visualization of it.
You don't mention whether this needs to be on prem or if it is OK if it runs somewhere else. Visual Studio Team Services work great for me. They also have hosted Mac instances that you can run on. It is very flexible. You can also install agents on your own machines to run on instead.
I've also used Bitrise in the past, it also has Mac OS and Linux machines where you can run your builds on.
I love bitrise, especially since it is free for OSS projects. This means I don't need a build server at home for iOS, whenever I need to build and release my iOS libraries. It is fast. It is flexible and gives you the possibility of making your build pipeline using their blocks and other OSS blocks around on GitHub. You can use build scripts such as Cake, Fake and many more. More importantly the guys behind bitrise are very helpful when encountering issues.
In Denmark we have two competing solutions. One is MobilePay, where you register your credit card and then you can make payments to contacts in your phone book which are also registered. It doesn't matter which bank you have. No fees, however there is a 2500 DKK limit of how much you can use and receive each day.
The other one is Swipp, which is a collaboration between all the small banks, which is integrated in their mobile banking apps, which kind of works as MobilePay, it is just tied directly to your account.
The MobilePay one is the most popular and stores have begun to accept that as payment as well, making it possible to use NFC or a QR code which you scan in the store when you check out. Some smaller stores just have a phone number you transfer money to. Works pretty well and has been for the past ~2 years.
On Android I use an App called Localcast, it can play directly from your device or from a network attached storage, DLNA or a link to a resource on the web. It also does Cloud storage such as Dropbox, Google Drive etc.
So it would seem like handoff to the Chromecast works really well. My TV supports Miracast and that does not work as well as the Chromecast does.
Thanks a lot. Yours is pretty cool too. However, I agree with other people saying that the element of the bubbles moving might not be the best indicator of frequency of mentions of that word in tweets.
Not sure, how it could be done otherwise, but it needs to be thought a bit more about. Maybe do something more to the bubbles, like coloring and filling them. Maybe even just showing a number inside the bubble if there is room, or when highlighted.
Also, instead of refreshing the page, you could consider something like Socket.io between the web page and your node.js server to update the values. There might be other alternatives to Socket.io, but then you won't have to refresh the entire page.
The Instagram pictures were there to back up the understanding of a hashtag generally. For under the world cup, it was really easy to find out what #worldcup2014 was about. Interestingly refreshing the page for a specific page during some kind of event, such as the world cup one, or during 24 Hours of Le Mans, it is easy to follow what people say about it. In the Le Mans case it was also quite easy to follow that for instanced someone crashed their as the sentiment drastically went to the negative side, and you could back that up with pictures of the crash on Instagram.
But I agree, a separate one analyzing the pictures could be valuable as well. However, Instagram pictures often don't contain much text apart from a wall of hash tags. So the text might not be super important to analyze. Anyways, picture analysis might be slightly more difficult and more resource intensive than text analysis, but very interesting as well.
A friend and I did something related to this in a project, where we attempted to analyze a hash tag, by fetching the latest 100 tweets about that hash tag. It is very useful in trending topics. For instance searching for "Stuart" right now reveals a lot of other relevant tags and attempts to find out what the general mood is of the words used in the tweets doing a simple Sentiment Analysis using AFINN. Try it here: http://hashtagram.dk/?t=stuart#hashtags (might get unavailable due to many visits, and don't mind the broken Instagram images at the bottom, site needs updating due to API changes). If for some reason the site does not work, see a static version here: http://imgur.com/EQzMrUP
Author describes a lot of features with words, but would have really been great if they added some images of what they are describing for better visualization of it.