Practical Text Analytics

Interpreting Text and Unstructured Data for Business Intelligence
1. Auflage 2015
ISBN: 978-0-7494-7401-0
Verlag: Kogan Page

Buch, Englisch, 272 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 418 g

Reihe: Marketing Science

In an age where customer opinion and feedback can have an immediate, major effect upon the success of a business or organization, marketers must have the ability to analyze unstructured data in everything from social media and internet reviews to customer surveys and phone logs. Practical Text Analytics is an essential daily reference resource, providing real-world guidance on the effective application of text analytics. The book presents the analysis process so that it is immediately understood by the marketing professionals who must use it, so they can apply proven concepts and methods correctly and with confidence. By decoding industry terminology and demonstrating practical application of data models once reserved for experts, Practical Text Analytics shows marketers how to frame the right questions, identify key themes and find hidden meaning from unstructured data. Readers will learn to develop powerful new marketing strategies to elevate customer experience, solidify brand value and elevate reputation. Online resources include self-test questions, chapter review Q&A and an Instructor's Manual with text sources and instructions.

Autoren/Hrsg.

Struhl, Steven

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Marketing
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management E-Commerce, E-Business, E-Marketing

Inhaltsverzeichnis

• • Chapter - 01: Who should read this book? And what do you want to do today?;
  • Chapter - 02: Getting ready: capturing, sorting, sifting, stemming and matching;
  • Chapter - 03: In pictures: word clouds, wordles and beyond;
  • Chapter - 04: Putting text together: clustering documents using words;
  • Chapter - 05: In the mood for sentiment (and counting) ;
  • Chapter - 06: Predictive models 1: having words with regressions;
  • Chapter - 07: Predictive models 2: classifications that grow on trees;
  • Chapter - 08: Predictive models 3: all in the family with Bayes Nets;
  • Chapter - 09: Looking forward and back

Über Autor(innen)

Struhl, Steven
<p><b>Dr. Steven Struhl </b>PhD, MBA, MA has more than 25 years' experience in consulting and research, specialising in practical solutions based on statistical models of decision-making and behaviour. In addition to text analytics and data mining, his work addresses how buying decisions are made, optimising service delivery and product configurations and finding the meaningful differences among products and services.

<b>Steven Struhl</b> also has taught graduate courses on statistical methods and data analysis. He speaks at conferences and has given numerous seminars on pricing, choice modelling, market segmentation and presenting data.</p>

Steven Struhl PhD, MBA, MA has more than 25 years' experience in consulting and research, specializing in practical solutions based on statistical models of decision-making and behaviour. In addition to text analytics and data mining, his work addresses how buying decisions are made, optimizing service delivery and product configurations and finding the meaningful differences among products and services. Steven also has taught graduate courses on statistical methods and data analysis. He speaks at conferences and has given numerous seminars on pricing, choice modelling, market segmentation and presenting data.