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: "social networks and social information filtering on digg"
  Abstract: The new social media sites -- blogs, wikis, Flickr and Digg, among others -- underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. Digg is a social news aggregator which allows users to submit links to, vote on and discuss news stories. Each day Digg selects a handful of stories to feature on its front page. Rather than rely on the opinion of a few editors, Digg aggregates opinions of thousands of its users to decide which stories to promote to the front page. #R##N#Digg users can designate other users as ``friends'' and easily track friends' activities: what new stories they submitted, commented on or read. The friends interface acts as a \emph{social filtering} system, recommending to user stories his or her friends liked or found interesting. By tracking the votes received by newly submitted stories over time, we showed that social filtering is an effective information filtering approach. Specifically, we showed that (a) users tend to like stories submitted by friends and (b) users tend to like stories their friends read and liked. As a byproduct of social filtering, social networks also play a role in promoting stories to Digg's front page, potentially leading to ``tyranny of the minority'' situation where a disproportionate number of front page stories comes from the same small group of interconnected users. Despite this, social filtering is a promising new technology that can be used to personalize and tailor information to individual users: for example, through personal front pages.

Connected through hyperedge HE-1 (induced by source paper "systems applications of social networks"):
  with members:
    - "a survey of signed network mining in social media"
    - "the architecture of innovation tracking face to face interactions with ubicomp technologies"
    - "social bootstrapping how pinterest and last fm social communities benefit by borrowing links from facebook"
    - "geo spotting mining online location based services for optimal retail store placement"
    - "social turing tests crowdsourcing sybil detection"
    - "explore what if scenarios with song social network write generator"
    - "uncovering social network sybils in the wild"
    - "empirical comparison of algorithms for network community detection"

Connected through hyperedge HE-2 (induced by source paper "using proximity to predict activity in social networks"):
  with members:
    - "what stops social epidemics"
    - "non conservative diffusion and its application to social network analysis"
    - "a probabilistic approach for learning folksonomies from structured data"
    - "birds of a feather does user homophily impact information diffusion in social media"
    - "stochastic models of user contributory web sites"
    - "novelty and collective attention"
    - "social information processing in news aggregation"
    - "social browsing on flickr"

Connected through hyperedge HE-3 (induced by source paper "using stochastic models to describe and predict social dynamics of web users"):
  with members:
    - "early warning analysis for social diffusion events"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "using a model of social dynamics to predict popularity of news"
    - "stochastic models of user contributory web sites"
    - "predicting the popularity of online content"
    - "analysis of social voting patterns on digg"
    - "novelty and collective attention"
    - "social information processing in news aggregation"

Connected through hyperedge HE-4 (induced by source paper "using a model of social dynamics to predict popularity of news"):
  with members:
    - "stochastic models of user contributory web sites"
    - "predicting the popularity of online content"
    - "analysis of social voting patterns on digg"
    - "novelty and collective attention"
    - "social information processing in news aggregation"
    - "social browsing on flickr"

Connected through hyperedge HE-5 (induced by source paper "stochastic models of user contributory web sites"):
  with members:
    - "predicting the popularity of online content"
    - "analysis of social voting patterns on digg"
    - "novelty and collective attention"
    - "social information processing in news aggregation"
    - "analysis of dynamic task allocation in multi robot systems"
    - "modeling and mathematical analysis of swarms of microscopic robots"

Connected through hyperedge HE-6 (induced by source paper "feedback loops of attention in peer production"):
  with members:
    - "crowdsourcing attention and productivity"
    - "predicting the popularity of online content"
    - "novelty and collective attention"

Connected through hyperedge HE-7 (induced by source paper "measurement and analysis of an online content voting network a case study of digg"):
  with members:
    - "analysis of social voting patterns on digg"
    - "rhythms of social interaction messaging within a massive online network"

Connected through hyperedge HE-8 (induced by source paper "personalizing image search results on flickr"):
  with members:
    - "empirical analysis of predictive algorithms for collaborative filtering"
    - "probabilistic models for unified collaborative and content based recommendation in sparse data environments"
    - "the author topic model for authors and documents"
    - "social browsing on flickr"
    - "the structure of collaborative tagging systems"
    - "content based book recommending using learning for text categorization"

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)