human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "what s in a github star understanding repository starring practices in a social coding platform"):
  Abstract: Abstract   Besides a git-based version control system, GitHub integrates several social coding features. Particularly, GitHub users can star a repository, presumably to manifest interest or satisfaction with an open source project. However, the real and practical meaning of starring a project was never the subject of an in-depth and well-founded empirical investigation. Therefore, we provide in this paper a throughout study on the meaning, characteristics, and dynamic growth of GitHub stars. First, by surveying 791 developers, we report that three out of four developers consider the number of stars before using or contributing to a GitHub project. Then, we report a quantitative analysis on the characteristics of the top-5,000 most starred GitHub repositories. We propose four patterns to describe stars growth, which are derived after clustering the time series representing the number of stars of the studied repositories; we also reveal the perception of 115 developers about these growth patterns. To conclude, we provide a list of recommendations to open source project managers (e.g., on the importance of social media promotion) and to GitHub users and Software Engineering researchers (e.g., on the risks faced when selecting projects by GitHub stars).

Includes members:
  Member "how do developers promote open source projects":
    also connected through other hyperedges:
      (none)
  Member "why modern open source projects fail":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "is this github project maintained measuring the level of maintenance activity of open source projects")
  Member "a novel approach for estimating truck factors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "refactoring graphs assessing refactoring over time")
  Member "predicting the popularity of github repositories":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "is this github project maintained measuring the level of maintenance activity of open source projects")
  Member "understanding the factors that impact the popularity of github repositories":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "is this github project maintained measuring the level of maintenance activity of open source projects")
  Member "why we refactor confessions of github contributors":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "refactoring graphs assessing refactoring over time")
  Member "dynamical classes of collective attention in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "language in our time an empirical analysis of hashtags")
  Member "robust classification for imprecise environments":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "is this github project maintained measuring the level of maintenance activity of open source projects")

Question: Please tell me which class the source paper 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.SE(Software Engineering)