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Data Mining Methods for the Content Analyst

This book review and resource compilation by Daniel Davies delves into data mining techniques for content analysts. It covers a range of topics including online databases, historic archives, newspaper archives, television news archives, website archives, development data, aggregated data sources, multimedia content utilization, and text analysis methods. The book discusses various steps in data processing such as extraction, cleaning, reformatting, and content proxy extraction with specific references. It also touches on speech recognition, OCR software, vocabulary analysis, readability indices, phonetic word accounts, vocabulary use correlation, geospatial value mapping, TIGER geocoding, latent semantic analysis, sentiment analysis, categorization, network analysis, and more.

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Data Mining Methods for the Content Analyst

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  1. Data Mining Methods for the Content Analyst Book Review & Resources - Daniel Davies

  2. Online Databases Historic Archives Newspaper Archives Television News Archives Newspaper Archives Website Archives Development Data Aggregated Data Sources Aggregated Data Sources

  3. Using Multimedia Content Prepare data 1. Extract 2. Clean 3. Reform /Reshape 4. Content Proxy Extraction (specific references) Speech Recognition OCR software Via Scribe - Speech Recognition OCR software

  4. Vocabulary Analysis Readability Index: Normative Comparison: Coleman Liau Index Gunning-fog Index Flesch-Kincaid Index Phonetic accounts of words Profile Vocab Use

  5. Correlation and Co-occurence Geo-spatial Value mapped lexicons Key Word in Context Index TIGER geocoding Latent Semantic Analysis International Geocoding Word relations

  6. Sentiment Analysis Categorization Network Analysis Dictionary of Affect in Language ATC - Automatic Text Categorization Citation Analysis & Bibbliometrics

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