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: "classification of message spreading in a heterogeneous social network"
  Abstract: Nowadays, social networks such as Twitter, Facebook and LinkedIn become increasingly popular. In fact, they introduced new habits, new ways of communication and they collect every day several information that have different sources. Most existing research works fo-cus on the analysis of homogeneous social networks, i.e. we have a single type of node and link in the network. However, in the real world, social networks offer several types of nodes and links. Hence, with a view to preserve as much information as possible, it is important to consider so-cial networks as heterogeneous and uncertain. The goal of our paper is to classify the social message based on its spreading in the network and the theory of belief functions. The proposed classifier interprets the spread of messages on the network, crossed paths and types of links. We tested our classifier on a real word network that we collected from Twitter, and our experiments show the performance of our belief classifier.

Connected through hyperedge HE-1 (induced by source paper "evidential positive opinion influence measures for viral marketing"):
  with members:
    - "two evidential data based models for influence maximization in twitter"
    - "maximizing positive opinion influence using an evidential approach"
    - "median evidential c means algorithm and its application to community detection"
    - "dynamic time warping distance for message propagation classification in twitter"
    - "a data based approach to social influence maximization"

Connected through hyperedge HE-2 (induced by source paper "two evidential data based models for influence maximization in twitter"):
  with members:
    - "adaptive imputation of missing values for incomplete pattern classification"
    - "median evidential c means algorithm and its application to community detection"
    - "dynamic time warping distance for message propagation classification in twitter"
    - "a data based approach to social influence maximization"

Connected through hyperedge HE-3 (induced by source paper "a survey of heterogeneous information network analysis"):
  with members:
    - "a survey of rdf data management systems"
    - "organizational chart inference"
    - "predicting neighbor distribution in heterogeneous information networks"
    - "pte predictive text embedding through large scale heterogeneous text networks"
    - "integrating heterogeneous information via flexible regularization framework for recommendation"
    - "scalable topical phrase mining from text corpora"
    - "future influence ranking of scientific literature"
    - "predicting social links for new users across aligned heterogeneous social networks"

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.SI(Social and Information Networks)