Let me know if there's anything else I can do to help in the meanwhile.
I'm here for you and want to see you be successful in all that you're doing with your social web mining pursuits!
However, I also recommend checking out my own handpicked collection of Essential Data Science books on Amazon. I personally own, have benefitted from all of these books, and have left brief comments to help you decide if any of them may be appropriate for your own personal enrichment.
O'Reilly Media's Data Science Starter Kit - http://bit.ly/18LmCfy
Essential Data Science Books (Amazon) - http://amzn.to/1bimqTp
If you have other essential recommendations, please leave a comment!
Check it out live:
Suggestions for future topics are welcome!
If you prefer collecting/reading books on the Kindle (or know someone who does), this is a great opportunity to pick up a copy.
See here for more details: http://amzn.to/1evWfrp
Thoughts or comments about how this book is being staged in the photo? Leave a comment! I'm curious what you think...
I'll also mail a signed copy to whoever comes up with the best caption for this photo by the end of the year. (If anyone is a Photoshop guru and wants to work some visual enhancements into play, it will likely bear strongly in the judging process...) Just leave a comment that is prefixed with "Caption" and you'll be eligible.
Happy holidays to everyone!
PS - As luck would have it, Mining the Social Web 2E is O'Reilly Media's Deal of the Day for today only and is 50% off until midnight PST. (Use code DEAL at checkout.)
PPS Guido likes it, and if it's good enough for Guido...well... :)
Happy Holidays to everyone!
(My results suggested that up to 50% of celebrity Twitter users (including Lady Gaga) are 'suspect' in the sense that they're spam-bots or abandoned accounts; more analysis is pending on a breakdown on the 'suspect' accounts with an update to follow.)
A snippet from the WSJ piece:
"Some entertainers pay for fake followers. But false accounts can be political tools as well. In 2011, thousands of fake accounts disrupted anti-Kremlin protesters on Twitter.
The fake accounts remain a cloud over Twitter Inc. in the wake of its successful initial public offering. 'Twitter is where many people get news,' says Sherry Turkle, director of the MIT Initiative on Technology and Self. 'If what is trending on Twitter is being faked by robots, people need to know that. This will and should undermine trust.'"
How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs.
- Employ IPython Notebook, the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites
- Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data
- Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects
- Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular "problem/solution/discussion" cookbook format
The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.