This master thesis explores to what degree information about a company's commitment to privacy can be extracted from a privacy statement. To do this, firstly a new database of more than 1500 privacy statements is created using Amazon Mechanical Turk. Next, 72 different aspects related to privacy of the statements are enumerated by using natural language processing. Multiple analyses are run on this data to look for signals which can indicate commitment to privacy. Ultimately, the analyses result in a number of ways which the quality and completeness can be assessed, and a method to find out the degree to which a privacy statement has likely copied other statements. This can be useful for privacy regulators in identifying companies which are less likely to comply with existing privacy regulations.