Binghamton University 3 credits INFO
The social Web is arguably the richest source of data in existence; however, collecting, managing, and analyzing social media data is not necessarily straightforward. While the Web is a mostly open and ubiquitous source of data, challenges like scale and ephemerality of data are challenges that must be overcome. Due to the heterogeneous nature of social media data, in terms of both acquisition methods and format, a sufficiently large toolbox of technologies and techniques must be used, including AI that combines technologies to enable real-time reliable communication, automate complex tasks, reduce time, labor, and effort, and minimize human intervention in decisions. Data scientists must make choices in terms of scalable data collection system architecture, extraction tools, and storage systems. While every data source is different, practical experience with tools and frameworks serves to provide the necessary foundation to design and implement the tools needed to collect any Web based data. Prerequisite: INFO 501, may be taken concurrently. Typically offered once every academic year. 3 credits.
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