The purpose of this study is to examine the retrieval performance of three search engines, specialized in retrieving news articles: News Index, Excite News Search and Ananova. Thirty questions, grouped into three categories – politics, economy and sports, were used and the first twenty documents for each question were examined. The questions used were designed to be as current as possible and efforts were made to perform the searches with as little time span as possible between each search engine. The precision of the search engines was determined for each of the questions as well as for each category and for the combined categories. In measuring precision an average was calculated, intended to favour search engines that place its relevant documents early in the ranked list. The relevance of the retrieved documents was evaluated using a three-grade scale. Irrelevant articles and duplicates were given 0 points, partially relevant documents were given 0,5 points and those judged to be highly relevant were given 1 point. The results of the study show surprisingly high precision from two of the search engines, Excite and News Index with the former performing slightly better than the latter. Ananova performed considerably worse than the other two. One possible reason for the high precision observed is the relatively low complexity of the documents retrieved compared to web pages in general. When comparing the different categories of questions one notable result was that all search engines performed considerably worse in the "economy"-category. Possible reasons for this are, apart from a higher number of duplicates, a shortage of relevant articles for the questions in this category as well as possible differences between either the documents retrieved in the different categories, or the web pages publishing them. / Uppsatsnivå: D