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: "supporting the use of user generated content in journalistic practice"
  Abstract: Social media and user-generated content (UGC) are increasingly important features of journalistic work in a number of different ways. However, their use presents major challenges, not least because information posted on social media is not always reliable and therefore its veracity needs to be checked before it can be considered as fit for use in the reporting of news. We report on the results of a series of in-depth ethnographic studies of journalist work practices undertaken as part of the requirements gathering for a prototype of a social media verification 'dashboard' and its subsequent evaluation. We conclude with some reflections upon the broader implications of our findings for the design of tools to support journalistic work.

Connected through hyperedge HE-1 (induced by source paper "the rumour mill making the spread of misinformation explicit and tangible"):
  with members:
    - "ctrl a conditional transformer language model for controllable generation"
    - "defending against neural fake news"
    - "anatomy of an online misinformation network"
    - "bots strongerin and brexit computational propaganda during the uk eu referendum"

Connected through hyperedge HE-2 (induced by source paper "a benchmark of visual storytelling in social media"):
  with members:
    - "barbara made the news mining the behavior of crowds for time aware learning to rank"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-3 (induced by source paper "detection and resolution of rumours in social media a survey"):
  with members:
    - "rumor detection and classification for twitter data"
    - "semeval 2017 task 8 rumoureval determining rumour veracity and support for rumours"
    - "simple open stance classification for rumour analysis"
    - "an efficient randomized algorithm for rumor blocking in online social networks"
    - "turing at semeval 2017 task 8 sequential approach to rumour stance classification with branch lstm"
    - "determining the veracity of rumours on twitter"
    - "hoaxy a platform for tracking online misinformation"
    - "contradiction detection for rumorous claims"

Connected through hyperedge HE-4 (induced by source paper "discourse aware rumour stance classification in social media using sequential classifiers"):
  with members:
    - "detection and resolution of rumours in social media a survey"
    - "semeval 2017 task 8 rumoureval determining rumour veracity and support for rumours"
    - "turing at semeval 2017 task 8 sequential approach to rumour stance classification with branch lstm"
    - "using gaussian processes for rumour stance classification in social media"
    - "sub story detection in twitter with hierarchical dirichlet processes"
    - "stance detection with bidirectional conditional encoding"
    - "stance classification in rumours as a sequential task exploiting the tree structure of social media conversations"
    - "learning reporting dynamics during breaking news for rumour detection in social media"

Connected through hyperedge HE-5 (induced by source paper "mining social media for newsgathering a review"):
  with members:
    - "detection and resolution of rumours in social media a survey"
    - "discourse aware rumour stance classification in social media using sequential classifiers"
    - "semeval 2017 task 8 rumoureval determining rumour veracity and support for rumours"
    - "fake news detection on social media a data mining perspective"
    - "discriminative predicate path mining for fact checking in knowledge graphs"
    - "hoaxy a platform for tracking online misinformation"
    - "rapid classification of crisis related data on social networks using convolutional neural networks"
    - "computational fact checking from knowledge networks"

Connected through hyperedge HE-6 (induced by source paper "stance classification of social media users in independence movements"):
  with members:
    - "towards real time country level location classification of worldwide tweets"
    - "happiness is assortative in online social networks"

Connected through hyperedge HE-7 (induced by source paper "microblog analysis as a programme of work"):
  with members:
    - "stance classification in rumours as a sequential task exploiting the tree structure of social media conversations"
    - "analysing how people orient to and spread rumours in social media by looking at conversational threads"
    - "towards detecting rumours in social media"
    - "who watches and shares what on youtube and when using twitter to understand youtube viewership"
    - "studying social networks at scale macroscopic anatomy of the twitter social graph"
    - "evolution of online user behavior during a social upheaval"
    - "traveling trends social butterflies or frequent fliers"
    - "mark my words linguistic style accommodation in social media"

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)