Figure 1: StoryPrint is an interactive visualization of script-based stories that plots scenes, character presence, and character emotion around a circular time axis.
Software development is becoming increasingly open and collaborative with the advent of platforms such as GitHub. Given its crucial role, there is a need to better understand and model the dynamics of GitHub as a social platform. Previous work has mostly considered the dynamics of traditional social networking sites like Twitter and Facebook. We propose GitEvolve, a system to predict the evolution of GitHub repositories and the different ways by which users interact with them. To this end, we develop an end-to-end multi-task sequential deep neural network that given some seed events, simultaneously predicts which user-group is next going to interact with a given repository, what the type of the interaction is, and when it happens. To facilitate learning, we use graph based representation learning to encode relationship between repositories. We map users to groups by modelling common interests to better predict popularity and to generalize to unseen users during inference. We introduce an artificial event type to better model varying levels of activity of repositories in the dataset. The proposed multi-task architecture is generic and can be extended to model information diffusion in other social networks. In a series of experiments, we demonstrate the effectiveness of the proposed model, using multiple metrics and baselines. Qualitative analysis of the model's ability to predict popularity and forecast trends proves its applicability 1 .
CCS CONCEPTS• Information systems → Social networks; • Computing methodologies → Neural networks; • Human-centered computing → Social networks.
JUNGLE is an interactive, visual platform for the collaborative manipulation and consumption of nonlinear transmedia stories. Intuitive visual interfaces encourage JUNGLE users to explore vast libraries of story worlds, expand existing stories, or conceive of entirely original story worlds. JUNGLE stories utilize multiple media forms including videos, images, and text, and accommodate branching narrative outcomes. We extensively evaluate Jungle using a focused small-scale study and free-form large-scale study with careful protection of study participant privacy. In the small-scale study, users found JUNGLE's features to be versatile, engaging, and intuitive for discovering new content. In the large-scale study, 354 subjects tested JUNGLE in a realistic 45-day scenario. We find that users collaborated on story worlds incorporating various forms of media in multiple (on average two) possible story paths. In particular, we find through initial observations that JUNGLE can evoke creativity: traditionally passive consumers gradually transition into active content creators. Supplementary videos showcasing the JUNGLE system and hypothetical example stories authored using JUNGLE independently hosted here and here.
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