In the digital age of polymedia (Madianou & Miller, 2012), a multitude of social media platforms provide youth with an endless menu of options, cultural expressions, imagery, metaphors, models, and narratives to tell the world (and themselves) who they are as they develop an autobiographical self (McAdams, 2013). To understand autobiographical selfdevelopment in the context of self-presentations on multiple platforms, we analyzed the structure and content of undergraduate college students' (N = 29, 17 = Female, 12 = Male, M age = 20) storytelling as they guided researchers on a tour of their three most frequently used social media platforms. Whole-person narrative analysis of audiovisual recordings of the social media tours revealed a variety of ways that young people construct themselves as real and recognizable in the context of master narratives surrounding authenticity and branding on social media (Davis, 2014;Marwick, 2013;Marwick & boyd, 2011). We present our insights into the process of constructing the autobiographical self as an authentic brand on social media through excerpts of stories youth tell about themselves and their experiences primarily on Twitter, Instagram, and Facebook.

Conversational systems typically focus on functional tasks such as scheduling appointments or creating todo lists. Instead we design and evaluate SlugBot (SB), one of 8 semifinalists in the 2018 Alexa Prize, whose goal is to support casual open-domain social interaction. This novel application requires both broad topic coverage and engaging interactive skills. We developed a new technical approach to meet this demanding situation by crowd-sourcing novel content and introducing playful conversational strategies based on storytelling and games. We collected over 10,000 conversations during August 2018 as part of the Alexa Prize competition. We also conducted an in-lab follow-up qualitative evaluation. Overall users found SB moderately engaging; conversations averaged 3.6 minutes and involved 26 user turns. However, users reacted very differently to different conversation subtypes. Storytelling and games were evaluated positively; these were seen as entertaining with predictable interactive structure. They also led users to impute personality and intelligence to SB. In contrast, search and general Chit-Chat induced coverage problems; here users found it hard to infer what topics SB could understand, with these conversations seen as being too system-driven. Theoretical and design implications suggest a move away from conversational systems that simply provide factual information. Future systems should be designed to have their own opinions with personal stories to share, and SB provides an example of how we might achieve this.