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: "you re mr lebowski i m the dude inducing address term formality in signed social networks"
  Abstract: We present an unsupervised model for inducing signed social networks from the content exchanged across network edges. Inference in this model solves three problems simultaneously: (1) identifying the sign of each edge; (2) characterizing the distribution over content for each edge type; (3) estimating weights for triadic features that map to theoretical models such as structural balance. We apply this model to the problem of inducing the social function of address terms, such as 'Madame', 'comrade', and 'dude'. On a dataset of movie scripts, our system obtains a coherent clustering of address terms, while at the same time making intuitively plausible judgments of the formality of social relations in each film. As an additional contribution, we provide a bootstrapping technique for identifying and tagging address terms in dialogue.

Connected through hyperedge HE-1 (induced by source paper "extraction and analysis of fictional character networks a survey"):
  with members:
    - "remembering winter was coming character oriented video summaries of tv series"
    - "conversational networks for automatic online moderation"
    - "remembering winter was coming"
    - "predicting kills in game of thrones using network properties"
    - "multilayer network model of movie script"
    - "from word to sense embeddings a survey on vector representations of meaning"
    - "i will be there for you six friends in a clique"
    - "the one comparing narrative social network extraction techniques"

Connected through hyperedge HE-2 (induced by source paper "tifi taxonomy induction for fictional domains extended version"):
  with members:
    - "integrating multiplicative features into supervised distributional methods for lexical entailment"
    - "hierarchical embeddings for hypernymy detection and directionality"
    - "taxonomy induction using hypernym subsequences"
    - "augur mining human behaviors from fiction to power interactive systems"
    - "relations such as hypernymy identifying and exploiting hearst patterns in distributional vectors for lexical entailment"
    - "hypernyms under siege linguistically motivated artillery for hypernymy detection"
    - "inferring interpersonal relations in narrative summaries"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-3 (induced by source paper "conversations gone awry detecting early signs of conversational failure"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "measuring gamergate a tale of hate sexism and bullying"
    - "asking too much the rhetorical role of questions in political discourse"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "interpreting neural networks to improve politeness comprehension"
    - "a piece of my mind a sentiment analysis approach for online dispute detection"
    - "ex machina personal attacks seen at scale"
    - "conversational markers of constructive discussions"

Connected through hyperedge HE-4 (induced by source paper "folksonomication predicting tags for movies from plot synopses using emotion flow encoded neural network"):
  with members:
    - "mpst a corpus of movie plot synopses with tags"
    - "the emotional arcs of stories are dominated by six basic shapes"
    - "hierarchical attention networks"
    - "recurrent models of visual attention"
    - "neural machine translation by jointly learning to align and translate"
    - "multiple object recognition with visual attention"
    - "from once upon a time to happily ever after tracking emotions in novels and fairy tales"
    - "crowdsourcing a word emotion association lexicon"

Connected through hyperedge HE-5 (induced by source paper "computational sociolinguistics a survey"):
  with members:
    - "confounds and consequences in geotagged twitter data"
    - "exploiting social network structure for person to person sentiment analysis"
    - "gender identity and lexical variation in social media"
    - "diffusion of lexical change in social media"
    - "efficient estimation of word representations in vector space"
    - "a computational approach to politeness with application to social factors"
    - "chameleons in imagined conversations a new approach to understanding coordination of linguistic style in dialogs"
    - "echoes of power language effects and power differences in social interaction"

Connected through hyperedge HE-6 (induced by source paper "inferring interpersonal relations in narrative summaries"):
  with members:
    - "modeling dynamic relationships between characters in literary novels"
    - "natural language processing almost from scratch"

Connected through hyperedge HE-7 (induced by source paper "modeling dynamic relationships between characters in literary novels"):
  with members:
    - "learning scripts as hidden markov models"
    - "probabilistic frame induction"

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)