Tag: Computer Information Science

Domain-Specific Heaven and Hell: A Matching Theory Method for Generating Permutations of a Popular Joke

Presenter : Noah Cooper

Mentor : Michael Hennessy

Major : Computer & Information Science

Poster 13

Heaven is where the police are English, the cooks are French, the mechanics are German, the lovers are Italian, and it’s all organized by the Swiss. Hell is where the police are German, the cooks are English, the mechanics are French, the lovers are Swiss, and it’s all organized by the Italians.” So goes the well-known joke reflecting some positive and negative stereotypes of European nations. Every intellectual community, too, has its famous methods, theories, and authors — each known for its merits as well as its shortcomings. So it would seem fertile ground for parodies of the European Heaven & Hell joke. But it turns out this joke has a peculiar structure that re- sists parody. My work analyzes that structure, demonstrating why an ad-hoc attempt at parody is prone to fail. It proposes an alternative algorithmic approach to generating parodies based on matching theory, a subfield of graph theory in finite mathematics. In so doing, I hope it makes some small contribution to the body of knowledge on computer-generated humor and the semantics of humor.“noise” produced by background turbulence may inhibit the capacity of the ctenophore to detect and respond to fluid motions produced by its prey.

Characterizing the Structure of Twitter Network Through Socially-Aware Clustering of Users

Presenter(s): Eugene Tan—Computer Information Science

Faculty Mentor(s): Reza Rejaie

Session: Prerecorded Poster Presentation

Popular online social networks (OSN) such as Twitter form a networked system where millions of users interconnect and exchange information . Characterizing the structural properties of the resulting”relationship graph” among the OSN users is very informative but inherently challenging because of its huge size and complex connectivity patterns . This project explores a novel “socially- aware” approach to classify Twitter users and thus partition the structure of Twitter relationship graph . To this end, we consider the top 10K most-followed Twitter users, called Twitter elite, and show that these users form coherent and socially meaningful communities, called Twitter elite communities . We define a “social interest vector” for each regular (i .e . non-elite) Twitter user where each element of this vector captures the user’s relative level of interest to a specific elite community based on the fraction of her followings in that elite community . We then rely on this multi-dimensional measure of user’s social interest to cluster millions of randomly selected Twitter users . We collect profile information, list of friends and followers along with available tweets for selected Twitter users in each cluster to assess (i) whether the resulting clusters of users are socially coherent, (ii) relative degree of connectivity between different pairs of clusters, and (iii) the key social attributes of each cluster . Overall, our analysis will illustrate if elite communities can serve as “landmarks” to meaningfully classify regular Twitter users and characterize the structure of the Twitter network .

Propagating Putative Prion States in RNA Modifying Proteins

Presenter(s): Jacob Evarts—Computer and Information Science

Faculty Mentor(s): David Garcia

Session: Prerecorded Poster Presentation

Prions have been closely associated with fatal neurodegenerative diseases such as mad cow disease . However, recent evidence suggests that prions provide an additional class of epigenetic mechanism that works at a rapid pace . From an evolutionary standpoint, the ability to change phenotypes without waiting for genetic variance would be hugely beneficial in a high stress environment . Using two known techniques for increasing de novo prion formation, protein overexpression and environmental stressor, we performed a large-scale screen across many RNA modifying enzymes in budding yeast . The growth dynamics presented here suggest that putative prion-state induction could be a widespread epigenetic mechanism across yeast .