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 "quantifying the effect of sentiment on information diffusion in social media"):
  Abstract: Social media has become the main vehicle of information production and consumption online. Millions of users every day log on their Facebook or Twitter accounts to get updates and news, read about their topics of interest, and become exposed to new opportunities and interactions. Although recent studies suggest that the contents users produce will affect the emotions of their readers, we still lack a rigorous understanding of the role and effects of contents sentiment on the dynamics of information diffusion. #R##N#This work aims at quantifying the effect of sentiment on information diffusion, to understand: #R##N#(i) whether positive conversations spread faster and/or broader than negative ones (or vice-versa); #R##N#(ii) what kind of emotions are more typical of popular conversations on social media; and, #R##N#(iii) what type of sentiment is expressed in conversations characterized by different temporal dynamics. #R##N#Our findings show that, at the level of contents, negative messages spread faster than positive ones, but positive ones reach larger audiences, suggesting that people are more inclined to share and favorite positive contents, the so-called positive bias. As for the entire conversations, we highlight how different temporal dynamics exhibit different sentiment patterns: for example, positive sentiment builds up for highly-anticipated events, while unexpected events are mainly characterized by negative sentiment. Our contribution represents a step forward to understand how the emotions expressed in short texts correlate with their spreading in online social ecosystems, and may help to craft effective policies and strategies for content generation and diffusion.

Includes members:
  Member "the rise of social bots":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a feature driven approach for identifying pathogenic social media accounts")
  Member "measuring emotional contagion in social media":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bots elections and social media a brief overview")
  Member "on predictability of rare events leveraging social media a machine learning perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring emotional contagion in social media")
  Member "on facebook most ties are weak":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the history of digital spam")
  Member "evolution of online user behavior during a social upheaval":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "can cascades be predicted":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep collaborative embedding for information cascade prediction")
  Member "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "locec local community based edge classification in large online social networks")
  Member "predicting successful memes using network and community structure":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a feature driven approach for identifying pathogenic social media accounts")

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)