Persona Generation from Social Media Analytics

Social media analytics is insightful, but it can also be difficult to use within organizations due to lack of analytics skills and empathy towards raw numbers portraying target groups. To address this concern, we present Automatic Persona Generation (APG), a system and methodology [1] for quantitatively generating personas using large amounts of online social media data (see Figure 1). To automatically generate personas from this data, APG methodology [2] applies a sequential approach, consisting of: • Identifying distinct user interaction patterns • Linking these patterns to demographic groups • Identifying impactful demographic groups from the data • Creating base personas via demographic attributes • Enriching these shell personas to create a complete persona 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. (see Figure 2). The APG system is operational and deployed with several organizations in multiple industry verticals. APG can be found online at https://persona.qcri.org.