The application of Big Data technology in various fields of humanities and social sciences in recent years has provided scholars with innovative ways and means to address the changing landscape of public opinion and political behavior. Although computer science has made, and continues to make, great progress both in terms of data management and in the development of analytical tools for handling vast amounts of data, problems of selection, measurement errors and other types of biases are still unsolved.
The research project Studying Opinions and Populations in Online Text Data seeks to validate the use of online text data as a complement to traditional surveys and polls. More specifically, we seek to develop computational methods for answering the following critical questions for scholars using online text data in conjunction with comparative survey data: 1) Is this text data relevant for my purposes?; 2) Is this text data reliable?; and 3) Is this text data representative of a population? The project contributes with important means for using online text data as a complement to traditional surveys and measures of public opinion as well as political attitudes and behaviours.