human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Evaluating Emotions in Mobile Application Descriptions: Sentiment Analysis Approach"
  Abstract: In this paper, we show how sentiment analysis can be used to detect emotions from mobile application descriptions which are persuasive text generated by software vendors. The analysis was conducted on a dataset containing 6,000 unique mobile apps. The results reveal that mobile app in different app category should use specific emotion words in the descriptions. This finding has interesting implications for practice especially for improving the chance that the app is downloaded or purchased.

Connected through hyperedge HE-1 (induced by source paper "Opinion Mining and Sentiment Analysis"):
  with members:
    - "Using Universal Linguistic Knowledge to Guide Grammar Induction"
    - "Opinion Mining and Information Fusion"
    - "Sentiment analysis in Facebook and its application to e-learning"
    - "Utility scoring of product reviews"
    - "Opinion observer: analyzing and comparing opinions on the Web"
    - "Mining newsgroups using networks arising from social behavior"
    - "User-level sentiment analysis incorporating social networks"
    - "Emotions and Information Diffusion in Social Media—Sentiment of Microblogs and Sharing Behavior"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science