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: "emojinet an open service and api for emoji sense discovery"
  Abstract: This paper presents the release of EmojiNet, the largest machine-readable emoji sense inventory that links Unicode emoji representations to their English meanings extracted from the Web. EmojiNet is a dataset consisting of: (i) 12,904 sense labels over 2,389 emoji, which were extracted from the web and linked to machine-readable sense definitions seen in BabelNet, (ii) context words associated with each emoji sense, which are inferred through word embedding models trained over Google News corpus and a Twitter message corpus for each emoji sense definition, and (iii) recognizing discrepancies in the presentation of emoji on different platforms, specification of the most likely platform-based emoji sense for a selected set of emoji. The dataset is hosted as an open service with a REST API and is available at this http URL The development of this dataset, evaluation of its quality, and its applications including emoji sense disambiguation and emoji sense similarity are discussed.

Connected through hyperedge HE-1 (induced by source paper "predictive analysis on twitter techniques and applications"):
  with members:
    - "what s my age predicting twitter user s age using influential friend network and dbpedia"
    - "multiview deep learning for predicting twitter users location"
    - "on the challenges of sentiment analysis for dynamic events"
    - "early detection of promoted campaigns on social media"
    - "location name extraction from targeted text streams using gazetteer based statistical language models"
    - "using social media to predict the future a systematic literature review"
    - "semi supervised approach to monitoring clinical depressive symptoms in social media"
    - "online human bot interactions detection estimation and characterization"

Connected through hyperedge HE-2 (induced by source paper "multimodal emotion classification"):
  with members:
    - "what s ur type contextualized classification of user types in marijuana related communications using compositional multiview embedding"
    - "which emoji talks best for my picture"
    - "learning emoji embeddings using emoji co occurrence network graph"
    - "multimodal emoji prediction"
    - "a semantics based measure of emoji similarity"
    - "fasttext zip compressing text classification models"
    - "finding street gang members on twitter"
    - "identity mappings in deep residual networks"

Connected through hyperedge HE-3 (induced by source paper "studying cultural differences in emoji usage across the east and the west"):
  with members:
    - "what twitter profile and posted images reveal about depression and anxiety"
    - "understanding and measuring psychological stress using social media"
    - "emoji2vec learning emoji representations from their description"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-4 (induced by source paper "which emoji talks best for my picture"):
  with members:
    - "leveraging knowledge bases in lstms for improving machine reading"
    - "the new modality emoji challenges in prediction anticipation and retrieval"
    - "what s ur type contextualized classification of user types in marijuana related communications using compositional multiview embedding"
    - "learning emoji embeddings using emoji co occurrence network graph"
    - "multimodal emoji prediction"
    - "a semantics based measure of emoji similarity"
    - "advances in pre training distributed word representations"
    - "are emojis predictable"

Connected through hyperedge HE-5 (induced by source paper "multimodal emoji prediction"):
  with members:
    - "the new modality emoji challenges in prediction anticipation and retrieval"
    - "exploring emoji usage and prediction through a temporal variation lens"
    - "through a gender lens learning usage patterns of emojis from large scale android users"
    - "spice up your chat the intentions and sentiment effects of using emoji"
    - "a semantics based measure of emoji similarity"
    - "are emojis predictable"
    - "emoji2vec learning emoji representations from their description"
    - "finding function in form compositional character models for open vocabulary word representation"

Connected through hyperedge HE-6 (induced by source paper "what s ur type contextualized classification of user types in marijuana related communications using compositional multiview embedding"):
  with members:
    - "predictive analysis on twitter techniques and applications"
    - "semantic structure and interpretability of word embeddings"
    - "verse versatile graph embeddings from similarity measures"
    - "attributed social network embedding"
    - "a semantics based measure of emoji similarity"
    - "advances in pre training distributed word representations"
    - "emojinet building a machine readable sense inventory for emoji"
    - "retrofitting word vectors to semantic lexicons"

Connected through hyperedge HE-7 (induced by source paper "exploring emoji usage and prediction through a temporal variation lens"):
  with members:
    - "the new modality emoji challenges in prediction anticipation and retrieval"
    - "multimodal emoji prediction"
    - "spice up your chat the intentions and sentiment effects of using emoji"
    - "a semantics based measure of emoji similarity"
    - "are emojis predictable"
    - "emoji2vec learning emoji representations from their description"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-8 (induced by source paper "self representation on twitter using emoji skin color modifiers"):
  with members:
    - "spice up your chat the intentions and sentiment effects of using emoji"

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.CL(Computation and Language)