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: "a long term analysis of polarization on twitter"
  Abstract: Social media has played an important role in shaping political discourse over the last decade. At the same time, it is often perceived to have increased political polarization, thanks to the scale of discussions and their public nature. #R##N#In this paper, we try to answer the question of whether political polarization in the US on Twitter has increased over the last eight years. We analyze a large longitudinal Twitter dataset of 679,000 users and look at signs of polarization in their (i) network - how people follow political and media accounts, (ii) tweeting behavior - whether they retweet content from both sides, and (iii) content - how partisan the hashtags they use are. Our analysis shows that online polarization has indeed increased over the past eight years and that, depending on the measure, the relative change is 10%-20%. Our study is one of very few with such a long-term perspective, encompassing two US presidential elections and two mid-term elections, providing a rare longitudinal analysis.

Connected through hyperedge HE-1 (induced by source paper "ideotrace a framework for ideology tracing with a case study on the 2016 u s presidential election"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "red bots do it better comparative analysis of social bot partisan behavior"
    - "predicting factuality of reporting and bias of news media sources"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "impact of social media posts in real life violence a case study in bangladesh"
    - "political discourse on social media echo chambers gatekeepers and the price of bipartisanship"
    - "who falls for online political manipulation"
    - "validation of twitter opinion trends with national polling aggregates hillary clinton vs donald trump"

Connected through hyperedge HE-2 (induced by source paper "online reactions to the 2017 unite the right rally in charlottesville measuring polarization in twitter networks using media followership"):
  with members:
    - "social network analysis for social neuroscientists"
    - "its all in a name detecting and labeling bots by their name"
    - "centrality in modular networks"
    - "a quantitative approach to understanding online antisemitism"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "on the origins of memes by means of fringe web communities"
    - "botornot a system to evaluate social bots"
    - "think locally act locally detection of small medium sized and large communities in large networks"

Connected through hyperedge HE-3 (induced by source paper "into the battlefield quantifying and modeling intra community conflicts in online discussion"):
  with members:
    - "how did the discussion go discourse act classification in social media conversations"
    - "multi task learning for target dependent sentiment classification"
    - "link prediction based on graph neural networks"
    - "community interaction and conflict on the web"
    - "an army of me sockpuppets in online discussion communities"
    - "semi supervised classification with graph convolutional networks"
    - "convolutional neural networks on graphs with fast localized spectral filtering"
    - "an ensemble method to produce high quality word embeddings"

Connected through hyperedge HE-4 (induced by source paper "tweeting mps digital engagement between citizens and members of parliament in the uk"):
  with members:
    - "mean birds detecting aggression and bullying on twitter"
    - "online human bot interactions detection estimation and characterization"
    - "botornot a system to evaluate social bots"
    - "content and network dynamics behind egyptian political polarization on twitter"

Connected through hyperedge HE-5 (induced by source paper "hot streaks on social media"):
  with members:
    - "exploring limits to prediction in complex social systems"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "the bursty dynamics of the twitter information network"

Connected through hyperedge HE-6 (induced by source paper "semi supervised graph labelling reveals increasing partisanship in the united states congress"):
  with members:
    - "debatenight the role and influence of socialbots on twitter during the 1st u s presidential debate"
    - "deepwalk online learning of social representations"

Connected through hyperedge HE-7 (induced by source paper "political discourse on social media echo chambers gatekeepers and the price of bipartisanship"):
  with members:
    - "balancing information exposure in social networks"
    - "the effect of collective attention on controversial debates on social media"
    - "limited individual attention and online virality of low quality information"
    - "reducing controversy by connecting opposing views"
    - "quantifying controversy in social media"
    - "partisan sharing facebook evidence and societal consequences"

Connected through hyperedge HE-8 (induced by source paper "me my echo chamber and i introspection on social media polarization"):
  with members:
    - "automatic detection and categorization of election related tweets"
    - "reducing controversy by connecting opposing views"
    - "measuring online social bubbles"
    - "designing and deploying online field experiments"

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)