Automatically conceptualizing social media analytics data via personas

• Main Authors: Jung S.G., Salminen J., An J., Kwak H., Jansen B.J.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: personas; data-driven personas; Databases and Information Systems; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/5342; https://ink.library.smu.edu.sg/context/sis_research/article/6346/viewcontent/17810_77996_1_PB.pdf
• Institution: Singapore Management University

Social media analytics is insightful but can also be difficult to use within organizations. To address this, we present Automatic Persona Generation (APG), a system and methodology for quantitatively generating personas using large amounts of online social media data. The APG system is operational, deployed in a pilot version with several organizations in multiple industry verticals. APG uses a robust web and stable back-end database framework to process tens of millions of user interactions with thousands of online digital products on multiple social media platforms, including Facebook and YouTube. APG identifies both distinct and impactful audience segments for an organization to create persona profiles by enhancing the social media analytics data with pertinent features, such as names, photos, interests, etc. We demonstrate the architecture development, and main system features. APG provides value for organizations distributing content via online platforms and is unique in its approach to leveraging social media data for audience understanding. APG is online at https://persona.qcri.org.