human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups authors who co-authored the same paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "WTF: the who to follow service at Twitter"):
  Abstract: WTF ("Who to Follow") is Twitter's user recommendation service, which is responsible for creating millions of connections daily between users based on shared interests, common connections, and other related factors. This paper provides an architectural overview and shares lessons we learned in building and running the service over the past few years. Particularly noteworthy was our design decision to process the entire Twitter graph in memory on a single server, which significantly reduced architectural complexity and allowed us to develop and deploy the service in only a few months. At the core of our architecture is Cassovary, an open-source in-memory graph processing engine we built from scratch for WTF. Besides powering Twitter's user recommendations, Cassovary is also used for search, discovery, promoted products, and other services as well. We describe and evaluate a few graph recommendation algorithms implemented in Cassovary, including a novel approach based on a combination of random walks and SALSA. Looking into the future, we revisit the design of our architecture and comment on its limitations, which are presently being addressed in a second-generation system under development.

Includes members:
  Member "Managing large dynamic graphs efficiently":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations")
  Member "Behavioral data mining to produce novel and serendipitous friend recommendations in a social bookmarking system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Guest Editorial: Behavioral-Data Mining in Information Systems and the Big Data Era")
  Member "Network Growth and Link Prediction Through an Empirical Lens":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "A local random walk model for complex networks based on discriminative feature combinations")

Question: Please tell me which research area the co-authored paper (i.e., the source paper of the center hyperedge) belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science