Opinion mining deals with scientific methods in order to find, extract and systematically analyze subjective information. When performing opinion mining to analyze content on the Web, challenges arise that usually do not occur in laboratory environments where prepared and preprocessed texts are used. This paper discusses preprocessing approaches that help coping with the emerging problems of sentiment analysis in real world situations. After outlining the identified shortcomings and presenting a general process model for opinion mining, promising solutions for language identification, content extraction and dealing with Internet slang are discussed.