human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "evomsa a multilingual evolutionary approach for sentiment analysis"):
  Abstract: Sentiment analysis (SA) is a task related to understanding people's feelings in written text; the starting point would be to identify the polarity level (positive, neutral or negative) of a given text, moving on to identify emotions or whether a text is humorous or not. This task has been the subject of several research competitions in a number of languages, e.g., English, Spanish, and Arabic, among others. In this contribution, we propose an SA system, namely EvoMSA, that unifies our participating systems in various SA competitions, making it domain independent and multilingual by processing text using only language-independent techniques. EvoMSA is a classifier, based on Genetic Programming, that works by combining the output of different text classifiers and text models to produce the final prediction. We analyze EvoMSA on different SA competitions to provide a global overview of its performance, and as the results show, EvoMSA is competitive obtaining top rankings in several SA competitions. Furthermore, we performed an analysis of EvoMSA's components to measure their contribution to the performance; the idea is to facilitate a practitioner or newcomer to implement a competitive SA classifier. Finally, it is worth to mention that EvoMSA is available as open-source software.

Includes members:
  Member "semeval 2017 task 4 sentiment analysis in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "related tasks can share a multi task framework for affective language")
  Member "amobee at semeval 2018 task 1 gru neural network with a cnn attention mechanism for sentiment classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "related tasks can share a multi task framework for affective language")
  Member "ug18 at semeval 2018 task 1 generating additional training data for predicting emotion intensity in spanish":
    also connected through other hyperedges:
      (none)
  Member "learning word vectors for 157 languages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "eitaka at semeval 2018 task 1 an ensemble of n channels convnet and xgboost regressors for emotion analysis of tweets":
    also connected through other hyperedges:
      (none)
  Member "seernet at semeval 2018 task 1 domain adaptation for affect in tweets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "related tasks can share a multi task framework for affective language")
  Member "bb_twtr at semeval 2017 task 4 twitter sentiment analysis with cnns and lstms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hybrid tiled convolutional neural networks for text sentiment classification")
  Member "niletmrg at semeval 2017 task 4 arabic sentiment analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a simple and effective approach for fine tuning pre trained word embeddings for improved text classification")

Question: Please tell me which class the source paper 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)