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: "gender asymmetries in reality and fiction the bechdel test of social media"
  Abstract: The subjective nature of gender inequality motivates the analysis and comparison of data from real and fictional human interaction. We present a computational extension of the Bechdel test: A popular tool to assess if a movie contains a male gender bias, by looking for two female characters who discuss about something besides a man. We provide the tools to quantify Bechdel scores for both genders, and we measure them in movie scripts and large datasets of dialogues between users of MySpace and Twitter. Comparing movies and users of social media, we find that movies and Twitter conversations have a consistent male bias, which does not appear when analyzing MySpace. Furthermore, the narrative of Twitter is closer to the movies that do not pass the Bechdel test than to those that pass it. #R##N#We link the properties of movies and the users that share trailers of those movies. Our analysis reveals some particularities of movies that pass the Bechdel test: Their trailers are less popular, female users are more likely to share them than male users, and users that share them tend to interact less with male users. Based on our datasets, we define gender independence measurements to analyze the gender biases of a society, as manifested through digital traces of online behavior. Using the profile information of Twitter users, we find larger gender independence for urban users in comparison to rural ones. Additionally, the asymmetry between genders is larger for parents and lower for students. Gender asymmetry varies across US states, increasing with higher average income and latitude. This points to the relation between gender inequality and social, economical, and cultural factors of a society, and how gender roles exist in both fictional narratives and public online dialogues.

Connected through hyperedge HE-1 (induced by source paper "analyzing gender inequality through large scale facebook advertising data"):
  with members:
    - "professional gender gaps across us cities"
    - "facebook use of sensitive data for advertising in europe"
    - "studying migrant assimilation through facebook interests"
    - "using facebook ads audiences for global lifestyle disease surveillance promises and limitations"
    - "fertility and its meaning evidence from search behavior"
    - "women through the glass ceiling gender asymmetries in wikipedia"
    - "evolution of privacy loss in wikipedia"

Connected through hyperedge HE-2 (induced by source paper "using data science to understand the film industry s gender gap"):
  with members:
    - "it s a man s wikipedia assessing gender inequality in an online encyclopedia"
    - "chameleons in imagined conversations a new approach to understanding coordination of linguistic style in dialogs"

Connected through hyperedge HE-3 (induced by source paper "gender matters analyzing global cultural gender preferences for venues using social sensing"):
  with members:
    - "it s a man s wikipedia assessing gender inequality in an online encyclopedia"
    - "first women second sex gender bias in wikipedia"
    - "the call of the crowd event participation in location based social services"
    - "you are what you eat and drink identifying cultural boundaries by analyzing food drink habits in foursquare"
    - "uncovering social network sybils in the wild"

Connected through hyperedge HE-4 (induced by source paper "the qwerty effect on the web how typing shapes the meaning of words in online human computer interaction"):
  with members:
    - "inferring networks of substitutable and complementary products"
    - "image based recommendations on styles and substitutes"
    - "sentiment cascades in the 15m movement"
    - "social signals and algorithmic trading of bitcoin"
    - "who watches and shares what on youtube and when using twitter to understand youtube viewership"
    - "from amateurs to connoisseurs modeling the evolution of user expertise through online reviews"
    - "positive words carry less information than negative words"
    - "happiness is assortative in online social networks"

Connected through hyperedge HE-5 (induced by source paper "gendered conversation in a social game streaming platform"):
  with members:
    - "gender productivity and prestige in computer science faculty hiring networks"
    - "it s a man s wikipedia assessing gender inequality in an online encyclopedia"
    - "document embedding with paragraph vectors"
    - "distributed representations of sentences and documents"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-6 (induced by source paper "it s a man s wikipedia assessing gender inequality in an online encyclopedia"):
  with members:
    - "who watches and shares what on youtube and when using twitter to understand youtube viewership"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"
    - "the tower of babel meets web 2 0 user generated content and its applications in a multilingual context"

Connected through hyperedge HE-7 (induced by source paper "first women second sex gender bias in wikipedia"):
  with members:
    - "it s a man s wikipedia assessing gender inequality in an online encyclopedia"
    - "moodbar increasing new user retention in wikipedia through lightweight socialization"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"

Connected through hyperedge HE-8 (induced by source paper "online privacy as a collective phenomenon"):
  with members:
    - "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook"
    - "social resilience in online communities the autopsy of friendster"
    - "a friendship privacy attack on friends and 2 distant neighbors in social networks"
    - "all liaisons are dangerous when all your friends are known to us"

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)