The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. We present a novel approach to metadata acquisition via Little Search Game (LSG) -a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. We describe specific aspects of the game's design, including player motivation and anti-cheating issues. We have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships.Keywords: Games with a purpose, human computation, crowdsourcing, metadata, semantics, search query, web search, term network INTRODUCTION Knowledge and semantics are needed both in quality and quantity. Many contemporary applications rely on (semantic) metadata in order to provide their intended functionality (Siorpaes & Simperl, 2010). Consequently, the creation or acquisition of such metadata is crucial to their effective operation and ultimately user satisfaction. Knowledge representations, from formal ontologies to lightweight taxonomies and flat folksonomy-like term networks, are especially vital to advanced information processing tasks that need to process semantic relationships between entities. Typical examples of applications are metadata-based search engines or faceted browsers , which require either document annotations or faceted classifications, (personalized) e-learning systems , which require complex course metadata, information repositories that need resource interlinks and annotations (e.g., Wikipedia), or Semantic Web applications that require formal ontologies. The use of concept relationships is also widely used in exploratory search tasks (Marchionini,