Average Reviews:
(More customer reviews)Kevin Roebuck's book contains a great deal of current information about sentiment analysis. A good thing, one would think, for those wanting to learn about this topic.
Not so much, if you are familiar with the Wikipedia web site. This book contains one hundred sixteen articles from Wikipedia on various topics related to sentiment analysis and text analysis generally. There is some very good information here. And all of it is available for free on the Wikipedia web site. This book's static capture of the web site will gradually drift out of date, but the site itself will live on, continually updated with the latest information. It will be there for anyone with web access.
Don't buy this book. Use the web site instead. In fact, don't buy any of the books in the High Impact Strategies series--just use Wikipedia online. I am sure that the author has worked out all of the copyright and permission issues to make this book legal. But it still seems shady to charge readers a hefty amount for a Kindle book built from free information. Granted, the author has done the work of identifying which Wikipedia articles are related to sentiment analysis. If he wanted a buck or two for that, I'd give it without squawking. But he asks a bit more.
A further recommendation: If you are interested in sentiment analysis, download the Kindle free sample for this book. Its table of contents is the list of Wikipedia articles the book contains. Use this list as a guide to Wikipedia's sentiment analysis information online. If you like, send a suitable donation DIRECTLY to Wikipedia. It's a worthy effort.
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Sentiment analysis or opinion mining refers to the application of natural language processing, computational linguistics, and text analytics to identify and extract subjective information in source materials.
Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall tonality of a document. The attitude may be his or her judgment or evaluation (see appraisal theory), affective state (that is to say, the emotional state of the author when writing), or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader).
This book is your ultimate resource for Sentiment Analysis. Here you will find the most up-to-date information, analysis, background and everything you need to know.
In easy to read chapters, with extensive references and links to get you to know all there is to know about Sentiment Analysis right away, covering: Sentiment analysis, Natural language processing, Affix grammar over a finite lattice, Afnlp, Aggregation (linguistics), Attensity, Automatic Acquisition of Sense-Tagged Corpora, Automatic summarization, Bag of words model, Bigram, Brill tagger, Cache language model, Calais (Reuters Product), ChaSen, ClearForest, Cmu Pronouncing Dictionary, Computational semantics, Computerized Speech Lab, Concept mining, Content determination, Controlled natural language, Cross-language information retrieval, Datr, Discourse relation, Document classification, Document-term matrix, Etblast, Filtered-popping recursive transition network, Robby Garner, GeneRif, Gorn address, Grammar checker, Grammar induction, Grammatik, History of machine translation, History of natural language processing, Iglue, Information extraction, Information retrieval, International Conference on Language Resources and Evaluation,
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