Searching for relevant webpages and following hyperlinks to related content is a widely accepted and effective approach to information seeking on the textual web. Existing work on multimedia information retrieval has focused on search for individual relevant items or on content linking without specific attention to search results. This presentation will describe work from the Search and Hyperlinking task of the MediaEval Mulitmedia Evaluation Benchmarking campaign. This task is exploring integrated multimodal search and hyperlinking of multimedia data. These investigations combine a known-item search task of video collections and a task examining the automatic creation of hyperlinks to link each relevant item to related items within the collection. The search test queries for this task are created and link relevance assessment carried out using the Amazon Mechanical Turk crowdsourcing platform. The presentation will describe the motivation and design of the tasks, and overview the alternative methods that task participants have introduced which seek to address the challenges of the tasks. The results of these experiments are being used to develop a research agenda for developing effective techniques for search and hyperlinking of multimedia content.