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 "white man and highly followed gender and race inequalities in twitter"):
  Abstract: Social media is considered a democratic space in which people connect and interact with each other regardless of their gender, race, or any other demographic factor. Despite numerous efforts that explore demographic factors in social media, it is still unclear whether social media perpetuates old inequalities from the offline world. In this paper, we attempt to identify gender and race of Twitter users located in U.S. using advanced image processing algorithms from Face++. Then, we investigate how different demographic groups (i.e. male/female, Asian/Black/White) connect with other. We quantify to what extent one group follow and interact with each other and the extent to which these connections and interactions reflect in inequalities in Twitter. Our analysis shows that users identified as White and male tend to attain higher positions in Twitter, in terms of the number of followers and number of times in user's lists. We hope our effort can stimulate the development of new theories of demographic information in the online space.

Includes members:
  Member "quantifying search bias investigating sources of bias for political searches in social media":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mining disinformation and fake news concepts methods and recent advancements")
  Member "demographics of news sharing in the u s twittersphere":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "gender and racial diversity in commercial brands advertising images on social media")
  Member "linguistic diversities of demographic groups in twitter":
    also connected through other hyperedges:
      (none)
  Member "who makes trends understanding demographic biases in crowdsourced recommendations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fairface face attribute dataset for balanced race gender and age")
  Member "from migration corridors to clusters the value of google data for migration studies":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sensing the chinese diaspora how mobile apps can provide insights into global migration flows")
  Member "women through the glass ceiling gender asymmetries in wikipedia":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "knowledge graphs")
  Member "greysanatomy vs yankees demographics and hashtag use on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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-7 (induced by source paper "the effects of gender signals and performance in online product reviews")

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)