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: "analyzing user activities demographics social network structure and user generated content on instagram"
  Abstract: Instagram is a relatively new form of communication where users can instantly share their current status by taking pictures and tweaking them using filters. It has seen a rapid growth in the number of users as well as uploads since it was launched in October 2010. Inspite of the fact that it is the most popular photo sharing application, it has attracted relatively less attention from the web and social media research community. In this paper, we present a large-scale quantitative analysis on millions of users and pictures we crawled over 1 month from Instagram. Our analysis reveals several insights on Instagram which were never studied before: 1) its social network properties are quite different from other popular social media like Twitter and Flickr, 2) people typically post once a week, and 3) people like to share their locations with friends. To the best of our knowledge, this is the first in-depth analysis of user activities, demographics, social network structure and user-generated content on Instagram.

Connected through hyperedge HE-1 (induced by source paper "language in our time an empirical analysis of hashtags"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "tagvisor a privacy advisor for sharing hashtags"
    - "hierarchical graph representation learning with differentiable pooling"
    - "you are your metadata identification and obfuscation of social media users using metadata information"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "ml leaks model and data independent membership inference attacks and defenses on machine learning models"
    - "twitter for sparking a movement reddit for sharing the moment metoo through the lens of social media"
    - "is saki delicious the food perception gap on instagram and its relation to health"

Connected through hyperedge HE-2 (induced by source paper "tagvisor a privacy advisor for sharing hashtags"):
  with members:
    - "knock knock who s there membership inference on aggregate location data"
    - "what does the crowd say about you evaluating aggregation based location privacy"
    - "walk2friends inferring social links from mobility profiles"
    - "back to the drawing board revisiting the design of optimal location privacy preserving mechanisms"
    - "fetishizing food in digital age foodporn around the world"
    - "deepcity a feature learning framework for mining location check ins"
    - "quantifying location sociality"
    - "dawn of the selfie era the whos wheres and hows of selfies on instagram"

Connected through hyperedge HE-3 (induced by source paper "measuring influence on instagram a network oblivious approach"):
  with members:
    - "online popularity and topical interests through the lens of instagram"

Connected through hyperedge HE-4 (induced by source paper "walk2friends inferring social links from mobility profiles"):
  with members:
    - "node2vec scalable feature learning for networks"
    - "deepcity a feature learning framework for mining location check ins"
    - "quantifying location sociality"
    - "line large scale information network embedding"
    - "deepwalk online learning of social representations"
    - "location prediction communities speak louder than friends"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-5 (induced by source paper "quantifying location sociality"):
  with members:
    - "smelly maps the digital life of urban smellscapes"
    - "measuring urban deprivation from user generated content"
    - "dawn of the selfie era the whos wheres and hows of selfies on instagram"
    - "topological properties and temporal dynamics of place networks in urban environments"
    - "the digital life of walkable streets"
    - "foodporn obesity patterns in culinary interactions"
    - "the shortest path to happiness recommending beautiful quiet and happy routes in the city"
    - "where businesses thrive predicting the impact of the olympic games on local retailers through location based services data"

Connected through hyperedge HE-6 (induced by source paper "deepcity a feature learning framework for mining location check ins"):
  with members:
    - "node2vec scalable feature learning for networks"
    - "line large scale information network embedding"
    - "the digital life of walkable streets"
    - "the shortest path to happiness recommending beautiful quiet and happy routes in the city"
    - "deepwalk online learning of social representations"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-7 (induced by source paper "sample nlpde and nlode social media modeling of information transmission for infectious diseases case study ebola"):
  with members:
    - "modeling information diffusion in online social networks with partial differential equations"
    - "analysis of a heterogeneous social network of humans and cultural objects"
    - "a computer virus propagation model using delay differential equations with probabilistic contagion and immunity"
    - "inheritance patterns in citation networks reveal scientific memes"
    - "statistically significant detection of linguistic change"
    - "do retweets indicate interest trust agreement extended abstract"
    - "a cooperate defect model for the spread of deviant behavior in social networks"
    - "what they do in shadows twitter underground follower market"

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)