The Lantern, 2016-2017

• Our Lady of Perpetual Virginity • Essential Terms for the Audience • Stories Untold • Jesus Camp • The Second Avenue Schmear • Driving to the Beach • Thanks, Alice • Decay • Peanut Butter Rhapsody • Transactions • Traffic • Sissy • Melting Wings • Ocean • Small Town Summer • Third Story • Family Trees • Mixed, Just Like Me • Sour Graves • How Sweet the Sound • Goodnight, Halfmoon • I\u27m Going to Ask Him How • Music • Pizza • Manhoodlike • Meditations From a Bunk Bed in a Home on Mount Pocono • Soft • Twilight\u27s Palette • The Oracle • Cynicism • River Ganges • Pinata Body and Hearing the Gun Shot • Song With No Music • Of Mornings Considering Womanhood • 10 Hours in Philadelphia • To Cut • Sachrang • Bavarian Wave Swinger • Irish Rain • Remembrances, Well • The Roses • Buttermilk • The Universe Will Always Listen if You Ask Her, Which is Why I Like Her More Than God • A Lukewarm Light • A Thought of Death • Hobson • Decaying Light • Window Women • Dead Bee • The Imagery • For Rent • Mona Lisa MMXVIhttps://digitalcommons.ursinus.edu/lantern/1185/thumbnail.jp

What If A Fish Got Drunk? Exploring the Plausibility of Machine-Generated Fictions

Within the WHIM project, we study fictional ideation: pro- cesses for automatically inventing, assessing and presenting fictional ideas. Here we examine the foundational notion of the plausibility of fictional ideas, by performing an empirical study to surface the factors that affect judgements of plau- sibility. Our long term aim is to formalise a computational method which captures some intuitive notions of plausibil- ity and can predict how certain types of people will assess the plausibility of certain types of fictional ideas. This paper constitutes a first firm step towards this aim