Online research methods are popular, dynamic and fast-changing. Following on from the great success of the first edition, published in 2008, The SAGE Handbook of Online Research Methods, Second Edition offers both updates of existing subject areas and new chapters covering more recent developments, such as social media, big data, data visualization and CAQDAS. Bringing together the leading names in both qualitative and quantitative online research, this new edition is organised into nine sections: 1. Online Research Methods 2. Designing Online Research 3. Online Data Capture and Data Collection 4. The Online Survey 5. Digital Quantitative Analysis 6. Digital Text Analysis 7. Virtual Ethnography 8. Online Secondary Analysis: Resources and Methods 9. The Future of Online Social Research The SAGE Handbook of Online Research Methods, Second Edition is an essential resource for anyone interested in the contemporary practice of computer-mediated research and scholarship.

Chapter 20: Sentiment Analysis for Small and Big Data

Sentiment Analysis for Small and Big Data

SENTIMENT ANALYSIS FOR SMALL AND BIG DATA
Mike Thelwall

Introduction

There are now effective methods to automatically detect sentiment in text and these are capable of human-like levels of performance in some contexts. These programs have been used primarily to analyse online texts, both for research and commercial applications, and are valuable to help gain insights into public opinions about the topics, products and issues discussed online. Automated sentiment analysis naturally has Big Data applications because it allows huge amounts of text to be processed rapidly, enabling sentiment-related insights to be gained about issues that might not otherwise be detectable with small amounts of data.

Opinion mining is concerned with developing software to automatically extract user opinions ...

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