Skip to Main Content
Information overload occurs when the information available exceeds the user's ability to process it. To manage information overload, a user is required to discriminate among useful, redundant, incorrect, and meaningless information. From a computer science perspective, this means we must provide users with a combination of techniques and tools for collecting, grouping, classifying, selecting, indexing, ranking, and filtering useful information. The articles in this special issue show four different facets of the information overload problem, by providing the readers with a big picture of the main research outcomes in this topic.