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 "demographics of news sharing in the u s twittersphere"):
  Abstract: The widespread adoption and dissemination of online news through social media systems have been revolutionizing many segments of our society and ultimately our daily lives. In these systems, users can play a central role as they share content to their friends. Despite that, little is known about news spreaders in social media. In this paper, we provide the first of its kind in-depth characterization of news spreaders in social media. In particular, we investigate their demographics, what kind of content they share, and the audience they reach. Among our main findings, we show that males and white users tend to be more active in terms of sharing news, biasing the news audience to the interests of these demographic groups. Our results also quantify differences in interests of news sharing across demographics, which has implications for personalized news digests.

Includes members:
  Member "what gets media attention and how media attention evolves over time large scale empirical evidence from 196 countries":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "what we read what we search media attention and public attention among 193 countries")
  Member "who makes trends understanding demographic biases in crowdsourced recommendations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fairface face attribute dataset for balanced race gender and age")
  Member "greysanatomy vs yankees demographics and hashtag use on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "whose tweets are surveilled for the police an audit of social media monitoring tool via log files")
  Member "inferring gender from names on the web a comparative evaluation of gender detection methods":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the effects of gender signals and performance in online product reviews")
  Member "it s a man s wikipedia assessing gender inequality in an online encyclopedia":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the effects of gender signals and performance in online product reviews")
  Member "breaking the news first impressions matter on online news":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sentiment dynamics in social media news channels")
  Member "when is it biased assessing the representativeness of twitter s streaming api":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "bias in data driven ai systems an introductory survey")
  Member "learning deep face representation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "quadruplet network with one shot learning for fast visual object tracking")

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)