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 "User-level sentiment analysis incorporating social networks"):
  Abstract: We show that information about social relationships can be used to improve user-level sentiment analysis. The main motivation behind our approach is that users that are somehow "connected" may be more likely to hold similar opinions; therefore, relationship information can complement what we can extract about a user's viewpoints from their utterances. Employing Twitter as a source for our experimental data, and working within a semi-supervised framework, we propose models that are induced either from the Twitter follower/followee network or from the network in Twitter formed by users referring to each other using "@" mentions. Our transductive learning results reveal that incorporating social-network information can indeed lead to statistically significant sentiment classification improvements over the performance of an approach based on Support Vector Machines having access only to textual features.

Includes members:
  Member "Opinion Mining and Sentiment Analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Deep Sparse Rectifier Neural Networks")
  Member "Mining newsgroups using networks arising from social behavior":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Opinion Mining and Sentiment Analysis")
  Member "PopMeter: Linked-Entities in a Sentiment Graph":
    also connected through other hyperedges:
      (none)

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