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: "persistent sharing of fitness app status on twitter"
  Abstract: As the world becomes more digitized and interconnected, information that was once considered to be private such as one's health status is now being shared publicly. To understand this new phenomenon better, it is crucial to study what types of health information are being shared on social media and why, as well as by whom. In this paper, we study the traits of users who share their personal health and fitness related information on social media by analyzing fitness status updates that MyFitnessPal users have shared via Twitter. We investigate how certain features like user profile, fitness activity, and fitness network in social media can potentially impact the long-term engagement of fitness app users. We also discuss implications of our findings to achieve a better retention of these users and to promote more sharing of their status updates.

Connected through hyperedge HE-1 (induced by source paper "does journaling encourage healthier choices analyzing healthy eating behaviors of food journalers"):
  with members:
    - "insights from machine learned diet success prediction"
    - "foodporn obesity patterns in culinary interactions"
    - "you tweet what you eat studying food consumption through twitter"

Connected through hyperedge HE-2 (induced by source paper "a warm welcome matters the link between social feedback and weight loss in r loseit"):
  with members:
    - "quantified self meets social media sharing of weight updates on twitter"
    - "the effect of social feedback in a reddit weight loss community"
    - "investigating causality in human behavior from smartphone sensor data a quasi experimental approach"
    - "how community feedback shapes user behavior"

Connected through hyperedge HE-3 (induced by source paper "achievement and friends key factors of player retention vary across player levels in online multiplayer games"):
  with members:
    - "exploring cyberbullying and other toxic behavior in team competition online games"
    - "the proficiency congruency dilemma virtual team design and performance in multiplayer online games"
    - "linguistic analysis of toxic behavior in an online video game"
    - "stfu noob predicting crowdsourced decisions on toxic behavior in online games"

Connected through hyperedge HE-4 (induced by source paper "insights from machine learned diet success prediction"):
  with members:
    - "you tweet what you eat studying food consumption through twitter"
    - "from cookies to cooks insights on dietary patterns via analysis of web usage logs"
    - "recipe recommendation using ingredient networks"

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)