Big Social Data: Approaches and Issues (3) Interdisciplinary integration of computational, informational, statistical, visual analytic, and social scientific approaches to the creation of big social data.
SO DA 501 Big Social Data: Approaches and Issues (3)
This seminar addresses the interdisciplinary integration of computational, informational, statistical, visual analytic, and social scientific approaches to the creation of data that are both "social" (about, or arising from, human interactions) and “big” (of sufficient scale, variety, or complexity to strain the informational, computational, or cognitive limits of conventional social scientific approaches to data collection or analysis). Examples include text, image, audio, video, intensive spatial and/or longitudinal data, data with complex network, hierarchical and/or other relational information, data from distributed sensors and mobile devices, digitized archival data, and data exhaust from sources like social media. Issues include sources of social data, data structures and formats for social data, data collection and manipulation technologies, data provenance, data linkage and alignment, ethics and scientific responsibility in human subjects research, experimental and observational data collection design for causal inference, sampling design, measurement of latent social concepts, reliability and validity, search and information retrieval, nonrelational and distributed databases, and standards for data preservation and sharing.
Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.