Students in social science courses communicate, socialize, shop, learn, and work online. When they are asked to collect data for course projects they are often drawn to social media platforms and other online sources of textual data. There are many software packages and programming languages available to help students collect data online, and there are many texts designed to help with different forms of online research, from surveys to ethnographic interviews. But there is no textbook available that teaches students how to construct a viable research project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives. Gabe Ignatow and Rada F. Mihalcea′s new text An Introduction to Text Mining will be a starting point for undergraduates and first-year graduate students interested in collecting and analyzing textual data from online sources, and will cover the most critical issues that students must take into consideration at all stages of their research projects, including: ethical and philosophical issues; issues related to research design; web scraping and crawling; strategic data selection; data sampling; use of specific text analysis methods; and report writing.

社会科学课程的学生在网上交流、社交、购物、学习和工作。当他们被要求为课程项目收集数据时，他们往往会被吸引到社交媒体平台和其他在线文本数据来源。有许多软件包和编程语言可以帮助学生在网上收集数据，也有许多文本旨在帮助进行不同形式的在线研究，从调查到人种学访谈。但目前还没有一本教科书教学生如何根据在线文本数据来源，如报纸档案、网站用户评论档案、数字化历史文件或社交媒体用户评论档案，构建一个可行的研究项目。Gabe Ignatow和Rada F. Mihalcea′的新书《文本挖掘导论》将成为对收集和分析在线来源的文本数据感兴趣的本科生和一年级研究生的起点，它将涵盖学生在研究项目的各个阶段必须考虑的最关键问题，包括：伦理和哲学问题；与研究设计有关的问题；网络刮擦和抓取；战略数据选择；数据采样；特定文本分析方法的使用；以及报告撰写。