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 the language of food on social media"
  Abstract: We investigate the predictive power behind the language of food on social media. We collect a corpus of over three million food-related posts from Twitter and demonstrate that many latent population characteristics can be directly predicted from this data: overweight rate, diabetes rate, political leaning, and home geographical location of authors. For all tasks, our language-based models significantly outperform the majority-class baselines. Performance is further improved with more complex natural language processing, such as topic modeling. We analyze which textual features have greatest predictive power for these datasets, providing insight into the connections between the language of food, geographic locale, and community characteristics. Lastly, we design and implement an online system for real-time query and visualization of the dataset. Visualization tools, such as geo-referenced heatmaps and temporal histograms, allow us to discover more complex, global patterns mirrored in the language of food.

Connected through hyperedge HE-1 (induced by source paper "scraping social media photos posted in kenya and elsewhere to detect and analyze food types"):
  with members:
    - "yolov3 an incremental improvement"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "is saki delicious the food perception gap on instagram and its relation to health"
    - "fetishizing food in digital age foodporn around the world"
    - "towards bottom up analysis of social food"
    - "aggregated residual transformations for deep neural networks"
    - "inception v4 inception resnet and the impact of residual connections on learning"
    - "densely connected convolutional networks"

Connected through hyperedge HE-2 (induced by source paper "you write like you eat stylistic variation as a predictor of social stratification"):
  with members:
    - "bleaching text abstract features for cross lingual gender prediction"
    - "reporting score distributions makes a difference performance study of lstm networks for sequence tagging"
    - "understanding and overcoming biases in customer reviews"
    - "multilingual part of speech tagging with bidirectional long short term memory models and auxiliary loss"
    - "distant supervision for emotion detection using facebook reactions"
    - "learning when to trust distant supervision an application to low resource pos tagging using cross lingual projection"
    - "computational sociolinguistics a survey"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-3 (induced by source paper "a survey on food computing"):
  with members:
    - "food recommendation framework existing solutions and challenges"
    - "learning cross modal embeddings with adversarial networks for cooking recipes and food images"
    - "recognition of multiple food items in a single photo for use in a buffet style restaurant"
    - "recipeqa a challenge dataset for multimodal comprehension of cooking recipes"
    - "scaling egocentric vision the epic kitchens dataset"
    - "rice classification using spatio spectral deep convolutional neural network"
    - "does journaling encourage healthier choices analyzing healthy eating behaviors of food journalers"
    - "single view food portion estimation learning image to energy mappings using generative adversarial networks"

Connected through hyperedge HE-4 (induced by source paper "you are what you eat a social media study of food identity"):
  with members:
    - "foodporn obesity patterns in culinary interactions"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-5 (induced by source paper "towards bottom up analysis of social food"):
  with members:
    - "foodporn obesity patterns in culinary interactions"
    - "very deep convolutional networks for large scale image recognition"
    - "training convolutional networks with noisy labels"
    - "you tweet what you eat studying food consumption through twitter"
    - "training deep neural networks on noisy labels with bootstrapping"

Connected through hyperedge HE-6 (induced by source paper "towards using social media to identify individuals at risk for preventable chronic illness"):
  with members:
    - "gender identity and lexical variation in social media"
    - "you tweet what you eat studying food consumption through twitter"
    - "the pulse of news in social media forecasting popularity"

Connected through hyperedge HE-7 (induced by source paper "foodporn obesity patterns in culinary interactions"):
  with members:
    - "you are what you eat and drink identifying cultural boundaries by analyzing food drink habits in foursquare"
    - "you tweet what you eat studying food consumption through twitter"

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.CL(Computation and Language)