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: "portrait of an online shopper understanding and predicting consumer behavior"
  Abstract: Consumer spending accounts for a large fraction of the US economic activity. Increasingly, consumer activity is moving to the web, where digital traces of shopping and purchases provide valuable data about consumer behavior. We analyze these data extracted from emails and combine them with demographic information to characterize, model, and predict consumer behavior. Breaking down purchasing by age and gender, we find that the amount of money spent on online purchases grows sharply with age, peaking in late 30s. Men are more frequent online purchasers and spend more money when compared to women. Linking online shopping to income, we find that shoppers from more affluent areas purchase more expensive items and buy them more frequently, resulting in significantly more money spent on online purchases. We also look at dynamics of purchasing behavior and observe daily and weekly cycles in purchasing behavior, similarly to other online activities. #R##N#More specifically, we observe temporal patterns in purchasing behavior suggesting shoppers have finite budgets: the more expensive an item, the longer the shopper waits since the last purchase to buy it. We also observe that shoppers who email each other purchase more similar items than socially unconnected shoppers, and this effect is particularly evident among women. Finally, we build a model to predict when shoppers will make a purchase and how much will spend on it. We find that temporal features improve prediction accuracy over competitive baselines. A better understanding of consumer behavior can help improve marketing efforts and make online shopping more pleasant and efficient.

Connected through hyperedge HE-1 (induced by source paper "when your friends become sellers an empirical study of social commerce site beidian"):
  with members:
    - "recommender systems with characterized social regularization"
    - "the role of social networks in online shopping information passing price of trust and consumer choice"

Connected through hyperedge HE-2 (induced by source paper "modeling interdependent and periodic real world action sequences"):
  with members:
    - "how gamification affects physical activity large scale analysis of walking challenges in a mobile application"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "harnessing the web for population scale physiological sensing a case study of sleep and performance"
    - "online actions with offline impact how online social networks influence online and offline user behavior"
    - "coevolve a joint point process model for information diffusion and network co evolution"
    - "modeling adoption and usage of competing products"

Connected through hyperedge HE-3 (induced by source paper "social media brand engagement as a proxy for e commerce activities a case study of sina weibo and jd"):
  with members:
    - "dynamical classes of collective attention in twitter"

Connected through hyperedge HE-4 (induced by source paper "computational social scientist beware simpson s paradox in behavioral data"):
  with members:
    - "can you trust the trend discovering simpson s paradoxes in social data"
    - "dynamics of content quality in collaborative knowledge production"
    - "information is not a virus and other consequences of human cognitive limits"
    - "evidence of online performance deterioration in user sessions on reddit"
    - "averaging gone wrong using time aware analyses to better understand behavior"
    - "the simple rules of social contagion"
    - "social dynamics of digg"
    - "what stops social epidemics"

Connected through hyperedge HE-5 (induced by source paper "iphone s digital marketplace characterizing the big spenders"):
  with members:
    - "the lifecycles of apps in a social ecosystem"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-6 (induced by source paper "information is not a virus and other consequences of human cognitive limits"):
  with members:
    - "the majority illusion in social networks"
    - "user effort and network structure mediate access to information in networks"
    - "the simple rules of social contagion"
    - "network weirdness exploring the origins of network paradoxes"
    - "friendship paradox redux your friends are more interesting than you"
    - "stochastic models predict user behavior in social media"
    - "information diffusion and external influence in networks"
    - "social dynamics of digg"

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)