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: "social media monitoring of the campaigns for the 2013 german bundestag elections on facebook and twitter"
  Abstract: As more and more people use social media to communicate their view and perception of elections,#R##N#researchers have increasingly been collecting and analyzing data from social media platforms.#R##N#Our research focuses on social media communication related to the 2013 election of the#R##N#German parliament [translation: Bundestagswahl 2013]. We constructed several social media#R##N#datasets using data from Facebook and Twitter. First, we identified the most relevant candidates#R##N#(n=2,346) and checked whether they maintained social media accounts. The Facebook data was#R##N#collected in November 2013 for the period of January 2009 to October 2013. On Facebook we#R##N#identified 1,408 Facebook walls containing approximately 469,000 posts. Twitter data was collected#R##N#between June and December 2013 finishing with the constitution of the government. On#R##N#Twitter we identified 1,009 candidates and 76 other agents, for example, journalists. We estimated#R##N#the number of relevant tweets to exceed eight million for the period from July 27 to September#R##N#27 alone. In this document we summarize past research in the literature, discuss possibilities#R##N#for research with our data set, explain the data collection procedures, and provide a description#R##N#of the data and a discussion of issues for archiving and dissemination of social media data.

Connected through hyperedge HE-1 (induced by source paper "race and religion in online abuse towards uk politicians working paper"):
  with members:
    - "partisanship propaganda and post truth politics quantifying impact in online debate"
    - "online abuse of uk mps from 2015 to 2019 working paper"
    - "tweeting mps digital engagement between citizens and members of parliament in the uk"
    - "lipstick on a pig debiasing methods cover up systematic gender biases in word embeddings but do not remove them"
    - "adversarial removal of demographic attributes from text data"
    - "reducing gender bias in abusive language detection"
    - "gender bias in coreference resolution evaluation and debiasing methods"
    - "semantics derived automatically from language corpora contain human like biases"

Connected through hyperedge HE-2 (induced by source paper "online abuse of uk mps from 2015 to 2019 working paper"):
  with members:
    - "lipstick on a pig debiasing methods cover up systematic gender biases in word embeddings but do not remove them"
    - "a large scale crowdsourced analysis of abuse against women journalists and politicians on twitter"
    - "adversarial removal of demographic attributes from text data"
    - "reducing gender bias in abusive language detection"
    - "gender bias in coreference resolution evaluation and debiasing methods"
    - "on fairness and calibration"
    - "semantics derived automatically from language corpora contain human like biases"
    - "equality of opportunity in supervised learning"

Connected through hyperedge HE-3 (induced by source paper "online abuse of uk mps in 2015 and 2017 perpetrators targets and topics"):
  with members:
    - "ex machina personal attacks seen at scale"
    - "analyzing the targets of hate in online social media"
    - "antisocial behavior in online discussion communities"
    - "emotional reactions and the pulse of public opinion measuring the impact of political events on the sentiment of online discussions"

Connected through hyperedge HE-4 (induced by source paper "systematically monitoring social media the case of the german federal election 2017"):
  with members:
    - "rising tides or rising stars dynamics of shared attention on twitter during media events"
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"

Connected through hyperedge HE-5 (induced by source paper "election campaigning on social media politicians audiences and the mediation of political communication on facebook and twitter"):
  with members:
    - "when politicians talk assessing online conversational practices of political parties on twitter"

Connected through hyperedge HE-6 (induced by source paper "when politicians talk assessing online conversational practices of political parties on twitter"):
  with members:
    - "semantic stability in social tagging streams"
    - "when politicians tweet a study on the members of the german federal diet"

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)