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: "eventful crowdsourcing local news reporting"
  Abstract: . Field reporters attend the events in person, and use Eventful's mobile web app to get a personalized mission, submit content, and receive fe edback. Missions include tasks such as taking a photo, and asking a question to an attendee. In parallel, remote curators approve, reject, and give real -time feedb ack on the content collected by field reporters. Finally, writers put together a report by mashing up and tweaking the content approved by the curators. We used Eventful to produce a news report for each of the six local events we decided to cover as we piloted the system. The process was typically completed under an hour and costing under $150 USD. Eventful is motivated by the desire to explore new mechanisms to fulfill the need for local journalism in a time when local news outlets struggle to survive. News organizations have reduced the resources devoted to report local events because revenue has declined [Pew 2010]. This absence of local news presents serious challenges to the health of local communities as it creates a vacuum of accountability for local government and businesses [Patterson 2007]. Professional journalism is a complex endeavor that we are not claiming to replace with Eventful. However, we are inspired by citizen journalism as a model that opens up new possibilities for non-experts to perform journalistic tasks. Citizen journalists have covered important events like terrorist attacks [Cassa et al. 2013] and revolutions [Lotan et al. 2011]. Even large news corporations, such as CNN [iReport] and The Guardian [Witness], have formalized the contributions of citizen journalists by inviting people to provide tips, photographs, and videos.

Connected through hyperedge HE-1 (induced by source paper "storia summarizing social media content based on narrative theory using crowdsourcing"):
  with members:
    - "newspad designing for collaborative storytelling in neighborhoods"

Connected through hyperedge HE-2 (induced by source paper "participatory militias an analysis of an armed movement s online audience"):
  with members:
    - "newspad designing for collaborative storytelling in neighborhoods"
    - "narco emotions affect and desensitization in social media during the mexican drug war"
    - "the new war correspondents the rise of civic media curation in urban warfare"
    - "smart societies from citizens as sensors to collective action"

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)