human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the proficiency congruency dilemma virtual team design and performance in multiplayer online games"
  Abstract: Multiplayer online battle arena games provide an excellent opportunity to study team performance. When designing a team, players must negotiate a \textit{proficiency-congruency dilemma} between selecting roles that best match their experience and roles that best complement the existing roles on the team. We adopt a mixed-methods approach to explore how users negotiate this dilemma. Using data from \textit{League of Legends}, we define a similarity space to operationalize team design constructs about role proficiency, generality, and congruency. We collect publicly available data from 3.36 million users to test the influence of these constructs on team performance. We also conduct focus groups with novice and elite players to understand how players' team design practices vary with expertise. We find that player proficiency increases team performance more than team congruency. These findings have implications for players, designers, and theorists about how to recommend team designs that jointly prioritize individuals' expertise and teams' compatibility.

Connected through hyperedge HE-1 (induced by source paper "the art of drafting a team oriented hero recommendation system for multiplayer online battle arena games"):
  with members:
    - "player skill decomposition in multiplayer online battle arenas"
    - "exploring cyberbullying and other toxic behavior in team competition online games"

Connected through hyperedge HE-2 (induced by source paper "achievement and friends key factors of player retention vary across player levels in online multiplayer games"):
  with members:
    - "exploring cyberbullying and other toxic behavior in team competition online games"
    - "persistent sharing of fitness app status on twitter"
    - "linguistic analysis of toxic behavior in an online video game"
    - "stfu noob predicting crowdsourced decisions on toxic behavior in online games"

Connected through hyperedge HE-3 (induced by source paper "an empirical study on team formation in online games"):
  with members:
    - "friends ftw friendship and competition in halo reach"
    - "friends ftw friendship and competition in halo reach"
    - "smote synthetic minority over sampling technique"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.HC(Human-Computer Interaction)