Computer Science | Grinnell College

On Friday, 3 October 2014, at CS Table, we will consider an intersection between computing and the arts, exploring the ways in which recommender systems can create experiences of serendipity. Alex Dodge, the College's Artist in Residence, will join us for the discussion.

Iaquinta, L., Gemmis, M. De, Lops, P., Semeraro, G., & Molino, P. (n.d.). Can a Recommender System induce serendipitous encounters?, 229–247. Read sections 1, 2, 3, and 4 (read further optionally). Available online at http://cdn.intechopen.com/pdfs-wm/10158.pdf.

Today recommenders are commonly used with various purposes, especially dealing with e- commerce and information filtering tools. Content-based recommenders rely on the concept of similarity between the bought/searched/visited item and all the items stored in a repository. It is a common belief that the user is interested in what is similar to what she has already bought/searched/visited. We believe that there are some contexts in which this assumption is wrong: it is the case of acquiring unsearched but still useful items or pieces of information. This is called serendipity. Our purpose is to stimulate users and facilitate these serendipitous encounters to happen.

Sun, T., & Mei, Q. (2012). Unexpected Relevance : An Empirical Study of Serendipity in Retweets. Read sections: Intro, Related Work, and Definition (read further optionally). Available online at http://www-personal.umich.edu/~qmei/pub/icwsm2013-sun.pdf.

Serendipity is a beneficial discovery that happens in an unexpected way. It has been found spectacularly valuable in various contexts, including scientific discoveries, acquisition of business, and recommender systems. Although never formally proved with large-scale behavioral analysis, it is believed by scientists and practitioners that serendipity is an important factor of positive user experience and increased user engagement. In this paper, we take the initiative to study the ubiquitous occurrence of serendipitious information diffusion and its effect in the context of microblogging communities. We refer to serendipity as unexpected relevance, then propose a principled statistical method to test the unexpectedness and the relevance of information received by a microblogging user, which identifies a serendipitous diffusion of information to the user. Our findings based on large-scale behavioral analysis reveal that there is a surprisingly strong presence of serendipitous information diffusion in retweeting, which accounts for more than 25% of retweets in both Twitter and Weibo. Upon the identification of serendipity, we are able to conduct observational analysis that reveals the benefit of serendipity to microblogging users. Results show that both the discovery and the provision of serendipity increase the level of user activities and social interactions, while the provision of serendipitous information also increases the influence of Twitter users.

The readings are available outside of Science 3821 or from Sam Rebelsky.

Computer science table is a weekly meeting of Grinnell College community members (students, faculty, staff, etc.) interested in discussing topics related to computing and computer science. CS Table meets Fridays from 12:10-12:50 in the Day PDR (JRC 224A). Contact Sam Rebelsky rebelsky@grinnell.edu for the weekly reading. Students on meal plans, faculty, and staff are expected to cover the cost of their meals. Students not on meal plans can charge their meals to the department.