Depending on what you're trying to do with the data, you may find http://diffbot.com/products/automatic/ helpful for getting the clean article text and categorization in JSON format. It can be used as a complement/augmentation to the great suggestions here for getting the links.
A lot of the commentary here is just shifting around the definition of networking--anywhere from attending public meetup events to "people skills".
The useful realization for an entrepreneur in a place like Silicon Valley is that networking is increasingly a commodity. The social graphs are so much more open and connected than before that anyone you'd want to meet is just one or two hops away. Thus, time and attention is better spent not on networking, but on the harder task of being a person of value to the network, so that other people will want to network with you.
The recent "duon" hype around there being a "2nd meaning of genetic sequences" isn't something scientists haven't know for a while. To take the analogy even further, there are regions of the genetic code for control flow (if/else/while/mutexes) and other regions with data (constants/numbers/strings), that make it into the final product.
Unfortunately, many machine learning algorithms aren't easily parallelizable. Consider any boosting ensemble learner, such as the popular random forest, which optimizes the result from the previous iteration. (I run the machine learning startup diffbot.com and we could really use faster cycles.)
you can essentially do this (post a twitter message from the address bar) in Chrome or Firefox without installing anything if you just configure a custom search engine with the path http://twitter.com/home?status=%s
1. In Chrome, go to Options > Default Search engine > Manage > Add
3. Now from the address bar, you can type: tweet [msg]
4. Forwards you to twitter. Although you still have to click a button on twitter, you could easily write your own serverside twitter API client that could post your tweet without the click.
Disclosure: Founder of Diffbot here.