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Mining the Social Web ペーパーバック – 2011/2/15
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Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover whos making connections with social media, what theyre talking about, and where theyre located. Youll learn how to combine social web data, analysis techniques, and visualization to find what youve been looking for in the social haystackas well as useful information you didnt know existed.
Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.
- Get a straightforward synopsis of the social web landscape
- Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+
- Learn how to employ easy-to-use Python tools to slice and dice the data you collect
- Explore social connections in microformats with the XHTML Friends Network
- Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection
- Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits
"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data."
--Alex Martelli, Senior Staff Engineer, Google
- 本の長さ360ページ
- 言語英語
- 出版社O′Reilly
- 発売日2011/2/15
- 寸法17.9 x 1.99 x 22.9 cm
- ISBN-101449388345
- ISBN-13978-1449388348
商品の説明
著者について
Matthew Russell, Vice President of Engineering at Digital Reasoning Systems (http://www.digitalreasoning.com/) and Principal at Zaffra (http://zaffra.com), is a computer scientist who is passionate about data mining, open source, and web application technologies. Hes also the author of Dojo: The Definitive Guide (OReilly).
登録情報
- 出版社 : O′Reilly; 第1版 (2011/2/15)
- 発売日 : 2011/2/15
- 言語 : 英語
- ペーパーバック : 360ページ
- ISBN-10 : 1449388345
- ISBN-13 : 978-1449388348
- 寸法 : 17.9 x 1.99 x 22.9 cm
- カスタマーレビュー:
著者について
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If you've never programmed at all, this book can be a bit intimidating. I suggest reading it through first just to understand what can be done, and then to dive back in selectively to play with some code and tools he introduces you to when you know what most interests you. Given the arcania of the academic discourse about Big Data, graph databases, etc., the author has done a very good job of de-mystifying as well as de-jargoning. As a result, this book is widely accessible for a broad audience.
If you're interested in this topic, there is no better book to start with.
In order to work with the book's examples related to LinkedIn and Facebook you really need to have a robust collection of connections. In terms of the source code itself, most of it worked as is. I wasn't able to install the Buzz library which limited my interaction with material in chapter 7 and opted to not get involved with the LinkedIn or Facebook but found the discussions around them easy to follow. By far my favorite chapter in the book was chapter 8, "Blogs et al.: Natural Language Processing (and Beyond)..." It was quite fascinating and caused my reading list to grow considerably.
Was mich allerdings sehr ärgert, ist die miserable Druckqualität, die ich von O'Reilly so nicht gewohnt bin. Seitenweise ist das Schriftbild nicht schwarz, sondern grau bis hellgrau, kursive Typen sind z.T. nicht mal komplett gedruckt. Das macht keinen Spaß, man hat das Gefühl mit einer billigen Kopie zu arbeiten. Ich hoffe nicht, dass das ein Trend wird - O'Reilly hat sich ja den Ruf erarbeitet, Bücher zu machen, die inhaltlich *und* von der Produktion her tadellos sind. Wird zurückgeschickt mit der Bitte um ein Exemplar mit *schwarzer* Schrift.
When originally attempting to enter this field, I found that I was overwhelmed with so many options in language, algorithm, business model, and catch phrase that I simply could not make progress. The beauty of this book is in its clear, concise progression from concept to concept that leaves the reader with a cohesive set of skills that are wildly marketable upon its completion.
The first friend I recommended this book to had almost no programming experience. 9 months later he landed a major deal mining social data for a major record label in Nashville.
Nuf said.
All the example codes I've tried so far had not worked.