People are highly opinionated and compelled to share with others. The advent of the social web has given them a tremendous new venue to do so, and explains, in part, the explosive growth in text data. These personal opinions are valuable; rather than being fleeting or trivial, they are both predictive of and caused by individual intentions. Over the last decade, scholars and practitioners of social media mining have developed techniques to measure and thus glean insights from textual opinion data. These tools are crucial, especially since much text data does not come with easily quantifiable opinions such as the availability of stars, likes, or thumbs-upsthat can be easily counted.

With the expanding availability of data and the increasing sophistication and usability of text data mining tools, social media mining is more accessible to a wide array of practitioners. An increasing number of social scientists, businesses, politicians, and media outlets put themselves at a stark disadvantage by ignoring this source of insight. Social scientists are now able to tap the sentiments of larger and harder-to-reach populations. Industries can now obtain granular reactions to products and adjust their offerings accordingly based on large samples, rather than a few poignant complaints. Politicians can gauge the desires of their constituents, the polarity of issues, and the effectiveness of their campaigns. Meanwhile, media outlets can not only track the interest in their stories, but also more easily take the pulse of the population on which they report.

The opinionated and plugged-in nature of people has driven the growth of text data; however, it is techniques like the ones outlined in this book that help add measurable value to that text. Techniques like the ones outlined in this book help explain the value of that text. Up until the last 40 years, these opinions were a part of small networks and shared mainly with first order neighbors. The data was hard if not impossible to collect, and few methods existed to examine the data. Nowadays, however, the data is available and the methods are maturing. We hope this book gives practitioners and scholars a quality entry point to the study and use of opinion mining techniques, and that it invests them with the knowledge necessary to explore textual data in a systematic and rigorous manner.