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 "domain specific sentiment word extraction by seed expansion and pattern generation"):
  Abstract: This paper focuses on the automatic extraction of domain-specific sentiment word (DSSW), which is a fundamental subtask of sentiment analysis. Most previous work utilizes manual patterns for this task. However, the performance of those methods highly relies on the labelled patterns or selected seeds. In order to overcome the above problem, this paper presents an automatic framework to detect large-scale domain-specific patterns for DSSW extraction. To this end, sentiment seeds are extracted from massive dataset of user comments. Subsequently, these sentiment seeds are expanded by synonyms using a bootstrapping mechanism. Simultaneously, a synonymy graph is built and the graph propagation algorithm is applied on the built synonymy graph. Afterwards, syntactic and sequential relations between target words and high-ranked sentiment words are extracted automatically to construct large-scale patterns, which are further used to extracte DSSWs. The experimental results in three domains reveal the effectiveness of our method.

Includes members:
  Member "a sentimental education sentiment analysis using subjectivity summarization based on minimum cuts":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sbert wk a sentence embedding method by dissecting bert based word models")
  Member "measuring praise and criticism inference of semantic orientation from association":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "revisiting paraphrase question generator using pairwise discriminator")
  Member "thumbs up sentiment classification using machine learning techniques":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "description based text classification with reinforcement learning")

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)