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 "tracking the history and evolution of entities entity centric temporal analysis of large social media archives"):
  Abstract: How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus meaningful analysis methods over such archived data are of immense value for sociologists, historians and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of four years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.

Includes members:
  Member "semeval 2016 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 "semeval 2017 task 4 sentiment analysis in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "related tasks can share a multi task framework for affective language")
  Member "tweetskb a public and large scale rdf corpus of annotated tweets":
    also connected through other hyperedges:
      (none)
  Member "time aware and corpus specific entity relatedness":
    also connected through other hyperedges:
      (none)
  Member "building and querying semantic layers for web archives extended version":
    also connected through other hyperedges:
      (none)
  Member "balancing novelty and salience adaptive learning to rank entities for timeline summarization of high impact events":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how to search the internet archive without indexing it")
  Member "learning from the news predicting entity popularity on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "predicting tomorrow s headline using today s twitter deliberations")
  Member "timeline generation tracking individuals on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generating timelines by modeling semantic change")

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.SI(Social and Information Networks)