In this post I want to pull together a couple of ideas around some of the measurable user activity generated as part of CFHE12. This will mainly focus around Twitter with some data from blog posts. I conclude that there are some simple opportunities to incorporate data from twitter into other channels, for example, summary of questions and retweets.
Twitter corpus for Sentiment Analysis from a class (cs224n)at Stanford.
Class page:
https://sites.google.com/site/twittersentimenthelp/for-researchers#Where_is_the_Tweet_corpus_8553
http://www.stanford.edu/~alecmgo/cs224n
LingPipe is tool kit for processing text using computational linguistics. LingPipe is used to do tasks like:
* Find the names of people, organizations or locations in news
* Automatically classify Twitter search results into categories
* Suggest correct spellings of queries
Truthy is a research project that helps you understand how memes spread online. We collect tweets from Twitter and analyze them. With our statistics, images, movies, and interactive data, you can explore these dynamic networks.
Our first application was the study of astroturf campaigns in elections. Currently, we're extending our focus to several themes. Browse the collection on the Memes page. Check out the Movie tool to browse and create animations of meme networks.
Twine is the simplest possible way to get the objects in your life texting, tweeting or emailing. A durable, battery-powered 2.5" square provides WiFi connectivity and internal and external sensors. A simple web app lets you quickly set up your Twine with human-friendly rules — no programming needed.
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