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: "mj no more using concurrent wikipedia edit spikes with social network plausibility checks for breaking news detection"
  Abstract: We have developed an application called Wikipedia Live Monitor that monitors article edits on different language versions of Wikipedia, as they happen in realtime. Wikipedia articles in different languages are highly interlinked. For example, the English article en:2013_Russian_meteor_event on the topic of the February 15 meteoroid that exploded over the region of Chelyabinsk Oblast, Russia, is interlinked with the Russian article on the same topic. As we monitor multiple language versions of Wikipedia in parallel, we can exploit this fact to detect concurrent edit spikes of Wikipedia articles covering the same topics, both in only one, and in different languages. We treat such concurrent edit spikes as signals for potential breaking news events, whose plausibility we then check with full-text cross-language searches on multiple social networks. Unlike the reverse approach of monitoring social networks first, and potentially checking plausibility on Wikipedia second, the approach proposed in this paper has the advantage of being less prone to false-positive alerts, while being equally sensitive to true-positive events, however, at only a fraction of the processing cost.

Connected through hyperedge HE-1 (induced by source paper "avoiding spoilers in fan wikis of episodic fiction"):
  with members:
    - "a framework for evaluation of composite memento temporal coherence"
    - "bringing web time travel to mediawiki an assessment of the memento mediawiki extension"
    - "evaluating sliding and sticky target policies by measuring temporal drift in acyclic walks through a web archive"
    - "memento time travel for the web"

Connected through hyperedge HE-2 (induced by source paper "telling breaking news stories from wikipedia with social multimedia a case study of the 2014 winter olympics"):
  with members:
    - "bots vs wikipedians anons vs logged ins"

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)