title: Bigger data for big data: from Twitter to brain-computer interfaces.
abstract: We are sympathetic with Bentley et al.'s attempt to encompass the wisdom of crowds in a generative model, but posit that a successful attempt at using big data will include more sensitive measurements, more varied sources of information, and will also build from the indirect information available through technology, from ancillary technical features to data from brain-computer interfaces.
authors.affiliation: School of Systems Engineering, University of Reading, Reading RG6 6AH, United Kingdom. contact@etienneroes.ch f.t.stahl@reading.ac.uk http://etienneroes.ch http://fredericstahl.wordpress.com.
authors.forename: Etienne B
authors.initials: EB
authors.lastname: Roesch
authors.affiliation: School of Systems Engineering, University of Reading, Reading RG6 6AH, United Kingdom. contact@etienneroes.ch f.t.stahl@reading.ac.uk http://etienneroes.ch http://fredericstahl.wordpress.com.
authors.forename: Frederic
authors.initials: F
authors.lastname: Stahl
authors.affiliation: School of Computing Science and Digital Media, The Robert Gordon University, Aberdeen AB25 1HG, United Kingdom. m.gaber1@rgu.ac.uk http://mohamedmgaber.weebly.com/
authors.forename: Mohamed Medhat
authors.initials: MM
authors.lastname: Gaber
mesh_terms: D003625:Data Collection; D003657:Decision Making; D006801:Humans; D012919:Social Behavior; D060756:Social Networking