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: "donor retention in online crowdfunding communities a case study of donorschoose org"
  Abstract: Online crowdfunding platforms like DonorsChoose.org and Kickstarter allow specific projects to get funded by targeted contributions from a large number of people. Critical for the success of crowdfunding communities is recruitment and continued engagement of donors. With donor attrition rates above 70%, a significant challenge for online crowdfunding platforms as well as traditional offline non-profit organizations is the problem of donor retention. #R##N#We present a large-scale study of millions of donors and donations on DonorsChoose.org, a crowdfunding platform for education projects. Studying an online crowdfunding platform allows for an unprecedented detailed view of how people direct their donations. We explore various factors impacting donor retention which allows us to identify different groups of donors and quantify their propensity to return for subsequent donations. We find that donors are more likely to return if they had a positive interaction with the receiver of the donation. We also show that this includes appropriate and timely recognition of their support as well as detailed communication of their impact. Finally, we discuss how our findings could inform steps to improve donor retention in crowdfunding communities and non-profit organizations.

Connected through hyperedge HE-1 (induced by source paper "user donations in a crowdsourced video system"):
  with members:
    - "representation learning on graphs methods and applications"
    - "understanding video ad consumption on youtube a measurement study on user behavior popularity and content properties"
    - "node2vec scalable feature learning for networks"
    - "line large scale information network embedding"
    - "deepwalk online learning of social representations"
    - "recommending investors for crowdfunding projects"

Connected through hyperedge HE-2 (induced by source paper "characterizing and forecasting user engagement with in app action graph a case study of snapchat"):
  with members:
    - "i know you ll be back interpretable new user clustering and churn prediction on a mobile social application"
    - "i ll be back on the multiple lives of users of a mobile activity tracking application"
    - "semi supervised classification with graph convolutional networks"
    - "moodbar increasing new user retention in wikipedia through lightweight socialization"
    - "user session identification based on strong regularities in inter activity time"

Connected through hyperedge HE-3 (induced by source paper "i ll be back on the multiple lives of users of a mobile activity tracking application"):
  with members:
    - "how gamification affects physical activity large scale analysis of walking challenges in a mobile application"
    - "online actions with offline impact how online social networks influence online and offline user behavior"
    - "wearable computing for health and fitness exploring the relationship between data and human behaviour"
    - "engaging with massive online courses"

Connected through hyperedge HE-4 (induced by source paper "identifying on time reward delivery projects with estimating delivery duration on kickstarter"):
  with members:
    - "how to succeed in crowdfunding a long term study in kickstarter"
    - "who will retweet this automatically identifying and engaging strangers on twitter to spread information"
    - "recommending investors for crowdfunding projects"

Connected through hyperedge HE-5 (induced by source paper "online actions with offline impact how online social networks influence online and offline user behavior"):
  with members:
    - "large scale analysis of counseling conversations an application of natural language processing to mental health"
    - "foodporn obesity patterns in culinary interactions"
    - "can cascades be predicted"
    - "how to ask for a favor a case study on the success of altruistic requests"
    - "the role of social networks in information diffusion"
    - "defining and evaluating network communities based on ground truth"
    - "information diffusion and external influence in networks"

Connected through hyperedge HE-6 (induced by source paper "large scale analysis of counseling conversations an application of natural language processing to mental health"):
  with members:
    - "how to ask for a favor a case study on the success of altruistic requests"
    - "distributed representations of words and phrases and their compositionality"
    - "echoes of power language effects and power differences in social interaction"
    - "catching the drift probabilistic content models with applications to generation and summarization"

Connected through hyperedge HE-7 (induced by source paper "user fluctuation in communities a forum case"):
  with members:
    - "evolution of conversations in the age of email overload"

Connected through hyperedge HE-8 (induced by source paper "how to succeed in crowdfunding a long term study in kickstarter"):
  with members:
    - "recommending investors for crowdfunding projects"

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.CY(Computers and Society)