Shared-memory Graph Truss Decomposition

We present PKT, a new shared-memory parallel algorithm and OpenMP implementation for the truss decomposition of large sparse graphs. A k-truss is a dense subgraph definition that can be considered a relaxation of a clique. Truss decomposition refers to a partitioning of all the edges in the graph based on their k-truss membership. The truss decomposition of a graph has many applications. We show that our new approach PKT consistently outperforms other truss decomposition approaches for a collection of large sparse graphs and on a 24-core shared-memory server. PKT is based on a recently proposed algorithm for k-core decomposition.Comment: 10 pages, conference submissio

Beauty and the Brand: A Digital Ethnography of Social Capital and Authenticity of Digital Beauty Influencers through Monetization Activities on YouTube

This dissertation explored the maintenance of social capital, projection of authenticity, alignment of beauty brands with the brand-as-person, and communicative practices of beauty influencers through a digital ethnography of YouTube beauty community. This research addressed how monetization practices by popular beauty influencers could affect the social constructs required in maintaining their position in the digital community. As beauty influencers continue to gain notoriety and engage in monetization activities through their standing on YouTube, it was important to address how the social practices utilized to build this notoriety were impacted by commoditization of content, toward understanding the sustainability of these practices for influencers and the beauty brands with whom they partner. A digital ethnography, utilizing an inductive content analysis and framework analysis, served as the method by which assessment of influencer projections and viewer reaction, within the cultural confines of the digital community, could be assessed. This research found that influencer projections were all impacted by the type of content. When influencers engaged in sponsored posts, viewers noted disparities in each of the constructs explored in this study, suggesting certain monetization activities can lower reputation engagement in the community. If influencers wish to engage in these monetization practices, they should be upfront with viewers about their intentions, choosing partnerships that are built through time and consistency. In doing so, influencers then are able to situate themselves as being genuine and honest with viewers, cementing their status in the community, while still benefitting personally and financially from monetization activities