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This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data.
Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence
C. Sun, L. Huang, and X. Qiu · 1903
Earlier work this paper cites.
Learning Fair Representations via an Adversarial Framework
R. Feng, Y. Yang, Y. Lyu, C. Tan, Y. Sun, and C. Wang · 1904
Earlier work this paper cites.
T. Manzini, Y. C. Lim, Y. Tsvetkov, and A. W. Black · 1904
Earlier work this paper cites.
Defending Against Neural Fake News
R. Zellers, A. Holtzman, H. Rashkin, Y. Bisk, A. Farhadi, F. Roesner, and Y. Choi · 1905
Earlier work this paper cites.
Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts
J. Bullock and M. Luengo-Oroz · 1906
Earlier work this paper cites.
Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classification
M. Hu, Y. Peng, Z. Huang, D. Li, and Y. Lv · 1906
Earlier work this paper cites.
Gender-preserving Debiasing for Pre-trained Word Embeddings
M. Kaneko and D. Bollegala · 1906
Earlier work this paper cites.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Y. Liu, M. Ott, N. Goyal, J. Du, M. Joshi, D. Chen, O. Levy, M. Lewis, L. Zettlemoyer, and V. Stoyanov · 1907
Earlier work this paper cites.
The Limitations of Stylometry for Detecting Machine-Generated Fake News
T. Schuster, R. Schuster, D. J. Shah, and R. Barzilay · 1908
Earlier work this paper cites.
Release Strategies and the Social Impacts of Language Models
I. Solaiman, M. Brundage, J. Clark, A. Askell, A. Herbert-Voss, J. Wu, A. Radford, G. Krueger, J. W. Kim, S. Kreps, M. McCain, A. Newhouse, J. Blazakis, K. McGuffie, and J. Wang · 1908
Earlier work this paper cites.
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
V. Sanh, L. Debut, J. Chaumond, and T. Wolf · 1910
Earlier work this paper cites.
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization
H. Jiang, P. He, W. Chen, X. Liu, J. Gao, and T. Zhao · 1911
Earlier work this paper cites.
On random graphs i
P. Erdős and A. Rényi · 1959
Earlier work this paper cites.
Models of segregation
T. C. Schelling · 1969
Earlier work this paper cites.
A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory
M. Fiedler · 1975
Earlier work this paper cites.
A general psychoevolutionary theory of emotion
R. Plutchik · 1980
Earlier work this paper cites.
Stochastic blockmodels: First steps
P. W. Holland, K. B. Laskey, and S. Leinhardt · 1983
Earlier work this paper cites.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
R. J. Williams · 1992
Earlier work this paper cites.
Toward principles for the design of ontologies used for knowledge sharing?
T. R. Gruber · 1995
Earlier work this paper cites.
An overview (and underview) of research and theory within the attraction paradigm
D. Byrne · 1997
Earlier work this paper cites.
Formal ontology in information systems: Proceedings of the first international conference (FOIS’98), June 6-8, Trento, Italy
N. Guarino · 1998
Earlier work this paper cites.
Collective dynamics of ‘small-world’networks
D. J. Watts and S. H. Strogatz · 1998
Earlier work this paper cites.
Emergence of scaling in random networks
A.-L. Barabási and R. Albert · 1999
Earlier work this paper cites.
Nonlinear dimensionality reduction by locally linear embedding
S. T. Roweis and L. K. Saul · 2000
Earlier work this paper cites.
Laplacian eigenmaps and spectral techniques for embedding and clustering
M. Belkin and P. Niyogi · 2001
Earlier work this paper cites.
Random graphs
B. Bollobás · 2001
Earlier work this paper cites.
Linguistic inquiry and word count: Liwc 2001
J. W. Pennebaker, M. E. Francis, and R. J. Booth · 2001
Earlier work this paper cites.
Community structure in social and biological networks
M. Girvan and M. E. J. Newman · 2002
Earlier work this paper cites.
Community structure in social and biological networks
M. Girvan and M. E. J. Newman · 2002
Earlier work this paper cites.
Hierarchical organization of modularity in metabolic networks
E. Ravasz, A. L. Somera, D. A. Mongru, Z. N. Oltvai, and A. L. Barabási · 2002
Earlier work this paper cites.
A core ontology for situation awareness
C. J. Matheus, M. M. Kokar, and K. Baclawski · 2003
Earlier work this paper cites.
Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence
F. Bianchi, S. Terragni, and D. Hovy · 2004
Earlier work this paper cites.
The diameter of a scale-free random graph
B. Bollobás and O. Riordan · 2004
Earlier work this paper cites.
Finding community structure in very large networks
A. Clauset, M. E. J. Newman, and C. Moore · 2004
Earlier work this paper cites.
GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media
Y.-J. Lu and C.-T. Li · 2004
Earlier work this paper cites.
Finding and evaluating community structure in networks
M. Newman and M. Girvan · 2004
Earlier work this paper cites.
Language Models are Few-Shot Learners
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei · 2005
Earlier work this paper cites.
Clique percolation in random networks
I. Derényi, G. Palla, and T. Vicsek · 2005
Earlier work this paper cites.
Graphs over time: densification laws, shrinking diameters and possible explanations
J. Leskovec, J. Kleinberg, and C. Faloutsos · 2005
Earlier work this paper cites.
Complex Graphs and Networks
F. Chung and L. Lu · 2006
Earlier work this paper cites.
W. Guo and A. Caliskan · 2006
Earlier work this paper cites.
Sampling from large graphs
J. Leskovec and C. Faloutsos · 2006
Earlier work this paper cites.
Resolution limit in community detection
S. Fortunato and M. Barthélemy · 2007
Earlier work this paper cites.
Resolution limit in community detection
S. Fortunato and M. Barthélemy · 2007
Earlier work this paper cites.
Graph evolution: Densification and shrinking diameters
J. Leskovec, J. Kleinberg, and C. Faloutsos · 2007
Earlier work this paper cites.
Near linear time algorithm to detect community structures in large-scale networks
N. Raghavan, R. Albert, and S. Kumara · 2007
Earlier work this paper cites.
Graph clustering
S. E. Schaeffer · 2007
Earlier work this paper cites.
Novelty and collective attention
F. Wu and B. A. Huberman · 2007
Earlier work this paper cites.
A spatial web graph model with local influence regions
W. Aiello, A. Bonato, C. Cooper, J. Janssen, and P. Prałat · 2008
Earlier work this paper cites.
Fast unfolding of communities in large networks
V. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre · 2008
Earlier work this paper cites.
Context Reinforced Neural Topic Modeling over Short Texts
J. Feng, Z. Zhang, C. Ding, Y. Rao, and H. Xie · 2008
Earlier work this paper cites.
Benchmark graphs for testing community detection algorithms
A. Lancichinetti, S. Fortunato, and F. Radicchi · 2008
Earlier work this paper cites.
Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks
S. Aral, L. Muchnik, and A. Sundararajan · 2009
Earlier work this paper cites.
Beyond microblogging: Conversation and collaboration via twitter
C. Honey and S. C. Herring · 2009
Earlier work this paper cites.
Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities
A. Lancichinetti and S. Fortunato · 2009
Earlier work this paper cites.
The Radicalization Risks of GPT-3 and Advanced Neural Language Models
K. McGuffie and A. Newhouse · 2009
Earlier work this paper cites.
The map equation
M. Rosvall, D. Axelsson, and C. Bergstrom · 2009
Earlier work this paper cites.
Relational learning via latent social dimensions
L. Tang and H. Liu · 2009
Earlier work this paper cites.
Link communities reveal multiscale complexity in networks
Y. Ahn, J. Bagrow, and S. Lehmann · 2010
Earlier work this paper cites.
Detecting spammers on twitter
F. Benevenuto, G. Magno, T. Rodrigues, and V. Almeida · 2010
Earlier work this paper cites.
Measuring user influence in twitter: The million follower fallacy
M. Cha, H. Haddadi, F. Benevenuto, and K. Gummadi · 2010
Earlier work this paper cites.
TopicBERT for Energy Efficient Document Classification
Y. Chaudhary, P. Gupta, K. Saxena, V. Kulkarni, T. Runkler, and H. Schütze · 2010
Earlier work this paper cites.
Community detection in graphs
S. Fortunato · 2010
Earlier work this paper cites.
Improving Neural Topic Models using Knowledge Distillation
A. Hoyle, P. Goel, and P. Resnik · 2010
Earlier work this paper cites.
Improving BERT Performance for Aspect-Based Sentiment Analysis
A. Karimi, L. Rossi, and A. Prati · 2010
Earlier work this paper cites.
Hyperbolic geometry of complex networks
D. Krioukov, F. Papadopoulos, M. Kitsak, A. Vahdat, and M. Boguñá · 2010
Earlier work this paper cites.
Topic Modeling with Contextualized Word Representation Clusters
L. Thompson and D. Mimno · 2010
Earlier work this paper cites.
Competition and multiscaling m evolving networks
G. Bianconi and A.-L. Barabási · 2011
Earlier work this paper cites.
The degree sequence of a scale-free random graph process
B. Bollobás, O. Riordan, J. Spencer, and G. Tusnády · 2011
Earlier work this paper cites.
Scale-free graphs of increasing degree
C. Cooper and P. Prałat · 2011
Earlier work this paper cites.
C. Dwork, M. Hardt, T. Pitassi, O. Reingold, and R. Zemel · 2011
Earlier work this paper cites.
On power-law relationships of the internet topology
M. Faloutsos, P. Faloutsos, and C. Faloutsos · 2011
Earlier work this paper cites.
Predicting personality from twitter
J. Golbeck, C. Robles, M. Edmondson, and K. Turner · 2011
Earlier work this paper cites.
It’s who you know: Graph mining using recursive structural features
K. Henderson, B. Gallagher, L. Li, L. Akoglu, T. Eliassi-Rad, H. Tong, and C. Faloutsos · 2011
Earlier work this paper cites.
Emergence of segregation in evolving social networks
A. D. Henry, P. Prałat, and C.-Q. Zhang · 2011
Earlier work this paper cites.
Random graphs
S. Janson, T. Luczak, and A. Rucinski · 2011
Earlier work this paper cites.
Automatic Detection of Machine Generated Text: A Critical Survey
G. Jawahar, M. Abdul-Mageed, and L. V. S. Lakshmanan · 2011
Earlier work this paper cites.
Our twitter profiles, our selves: Predicting personality with twitter
D. Quercia, M. Kosinski, D. Stillwell, and J. Crowcroft · 2011
Earlier work this paper cites.
Co-author relationship prediction in heterogeneous bibliographic networks
Y. Sun, R. Barber, M. Gupta, C. C. Aggarwal, and J. Han · 2011
Earlier work this paper cites.
Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
H. Xu, L. Shu, P. S. Yu, and B. Liu · 2011
Earlier work this paper cites.
Extracting Training Data from Large Language Models
N. Carlini, F. Tramer, E. Wallace, M. Jagielski, A. Herbert-Voss, K. Lee, A. Roberts, T. Brown, D. Song, U. Erlingsson, A. Oprea, and C. Raffel · 2012
Earlier work this paper cites.
Dynamical classes of collective attention in twitter
J. Lehmann, B. Gonçalves, J. J. Ramasco, and C. Cattuto · 2012
Earlier work this paper cites.
When will it happen? relationship prediction in heterogeneous information networks
Y. Sun, J. Han, C. C. Aggarwal, and N. V. Chawla · 2012
Earlier work this paper cites.
Evaluating Topic Coherence Using Distributional Semantics
N. Aletras and M. Stevenson · 2013
Earlier work this paper cites.
Gate teamware: a web-based, collaborative text annotation framework
K. Bontcheva, H. Cunningham, I. Roberts, A. Roberts, V. Tablan, N. Aswani, and G. Gorrell · 2013
Earlier work this paper cites.
Large-scale visual sentiment ontology and detectors using adjective noun pairs
D. Borth, R. Ji, T. Chen, T. Breuel, and S.-F. Chang · 2013
Earlier work this paper cites.
Evolution of networks: From biological nets to the Internet and WWW
S. N. Dorogovtsev and J. F. Mendes · 2013
Earlier work this paper cites.
A measure of polarization on social media networks based on community boundaries
P. Guerra, W. Meira Jr, C. Cardie, and R. Kleinberg · 2013
Earlier work this paper cites.
An introduction to exponential random graph modeling
J. K. Harris · 2013
Cited alongside, same era.
Birds of a feather tweet together: Integrating network and content analyses to examine cross-ideology exposure on twitter
I. Himelboim, S. McCreery, and M. Smith · 2013
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean · 2013
Cited alongside, same era.
Crowdsourcing a word-emotion association lexicon
S. M. Mohammad and P. D. Turney · 2013
Cited alongside, same era.
Generalized preferential attachment: tunable power-law degree distribution and clustering coefficient
L. Ostroumova, A. Ryabchenko, and E. Samosvat · 2013
Cited alongside, same era.
Utterance-Level Multimodal Sentiment Analysis
V. Pérez-Rosas, R. Mihalcea, and L.-P. Morency · 2013
Generative Models for Spear Phishing Posts on Social Media
J. Seymour and P. Tully · 2018
Later among the works it cites.
Multi-institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation
M. J. Sheller, G. A. Reina, B. Edwards, J. Martin, and S. Bakas · 2018
Later among the works it cites.
Beyond News Contents: The Role of Social Context for Fake News Detection
K. Shu, S. Wang, and H. Liu · 2018
Later among the works it cites.
EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection
Y. Wang, F. Ma, Z. Jin, Y. Yuan, G. Xun, K. Jha, L. Su, and J. Gao · 2018
Later among the works it cites.
Computational propaganda: political parties, politicians, and political manipulation on social media
S. C. Woolley and P. N. Howard · 2018
Later among the works it cites.
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Cited alongside, same era.
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
R. Socher, A. Perelygin, J. Wu, J. Chuang, C. D. Manning, A. Ng, and C. Potts · 2013
Cited alongside, same era.
Webanno: A flexible, web-based and visually supported system for distributed annotations
S. M. Yimam, I. Gurevych, R. E. de Castilho, and C. Biemann · 2013
Cited alongside, same era.
Who to follow and why: link prediction with explanations
N. Barbieri, F. Bonchi, and G. Manco · 2014
Cited alongside, same era.
Deepsentibank: Visual sentiment concept classification with deep convolutional neural networks
T. Chen, D. Borth, T. Darrell, and S.-F. Chang · 2014
Cited alongside, same era.
Some typical properties of the spatial preferred attachment model
C. Cooper, A. Frieze, and P. Prałat · 2014
Cited alongside, same era.
Navigability of interconnected networks under random failures
M. De Domenico, A. Solé-Ribalta, S. Gómez, and A. Arenas · 2014
Cited alongside, same era.
Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate
L. Wu and H. Liu · 2018
Later among the works it cites.
Network representation learning: A survey
D. Zhang, J. Yin, X. Zhu, and C. Zhang · 2018
Later among the works it cites.
Deeplink: A deep learning approach for user identity linkage
F. Zhou, L. Liu, K. Zhang, G. Trajcevski, J. Wu, and T. Zhong · 2018
Later among the works it cites.
Learning Semantic Coherence for Machine Generated Spam Text Detection
M. Bao, J. Li, J. Zhang, H. Peng, and X. Liu · 2019
Later among the works it cites.
Multiplex and Multilevel Networks
S. Battiston, G. Caldarelli, and A. Garas, editors · 2019
Later among the works it cites.
Social profiling: A review, taxonomy, and challenges
M. Bilal, A. Gani, M. I. U. Lali, M. Marjani, and N. Malik · 2019
Later among the works it cites.
Towards federated learning at scale: System design
K. Bonawitz, H. Eichner, W. Grieskamp, D. Huba, A. Ingerman, V. Ivanov, C. Kiddon, J. Konečnỳ, S. Mazzocchi, H. B. McMahan, et al · 2019
Later among the works it cites.
Hyperbolic graph convolutional neural networks
I. Chami, Z. Ying, C. Ré, and J. Leskovec · 2019
Later among the works it cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2019
Later among the works it cites.
Relationship prediction in dynamic heterogeneous information networks
A. M. Fard, E. Bagheri, and K. Wang · 2019
Later among the works it cites.
Hypergraph neural networks
Y. Feng, H. You, Z. Zhang, R. Ji, and Y. Gao · 2019
Later among the works it cites.
Stochastic block models: A comparison of variants and inference methods
T. Funke and T. Becker · 2019
Later among the works it cites.
What twitter profile and posted images reveal about depression and anxiety
S. C. Guntuku, D. Preotiuc-Pietro, J. C. Eichstaedt, and L. H. Ungar · 2019
Later among the works it cites.
TextKD-GAN: Text Generation Using Knowledge Distillation and Generative Adversarial Networks
M. A. Haidar and M. Rezagholizadeh · 2019
Later among the works it cites.
Clustering via hypergraph modularity
B. Kamiński, V. Poulin, P. Prałat, P. Szufel, and F. Théberge · 2019
Later among the works it cites.
MVAE: Multimodal Variational Autoencoder for Fake News Detection
D. Khattar, J. S. Goud, M. Gupta, and V. Varma · 2019
Later among the works it cites.
A new measure of modularity in hypergraphs: Theoretical insights and implications for effective clustering
T. Kumar, S. Vaidyanathan, H. Ananthapadmanabhan, S. Parthasarathy, and B. Ravindran · 2019
Later among the works it cites.
jcpeterson/openwebtext, June 2021
J. C. Peterson · 2019
Later among the works it cites.
Ensemble clustering for graphs: comparisons and applications
V. Poulin and F. Théberge · 2019
Later among the works it cites.
dEFEND: Explainable Fake News Detection
K. Shu, L. Cui, S. Wang, D. Lee, and H. Liu · 2019
Later among the works it cites.
Influence of augmented humans in online interactions during voting events
M. Stella, M. Cristoforetti, and M. De Domenico · 2019
Later among the works it cites.
From louvain to leiden: guaranteeing well-connected communities
V. Traag, L. Waltman, and N. van Eck · 2019
Later among the works it cites.
A survey of across social networks user identification
L. Xing, K. Deng, H. Wu, P. Xie, H. V. Zhao, and F. Gao · 2019
Later among the works it cites.
Federated machine learning: Concept and applications
Q. Yang, Y. Liu, T. Chen, and Y. Tong · 2019
Later among the works it cites.
A survey of sentiment analysis in social media
L. Yue, W. Chen, X. Li, W. Zuo, and M. Yin · 2019
Later among the works it cites.
Federated learning: A survey on enabling technologies, protocols, and applications
M. Aledhari, R. Razzak, R. M. Parizi, and F. Saeed · 2020
Later among the works it cites.
Top2vec: Distributed representations of topics, 2020
D. Angelov · 2020
Later among the works it cites.
Effectiveness of dismantling strategies on moderated vs. unmoderated online social platforms
O. Artime, V. d’Andrea, R. Gallotti, P. L. Sacco, and M. De Domenico · 2020
Later among the works it cites.
Assessing the russian internet research agency’s impact on the political attitudes and behaviors of american twitter users in late 2017
C. A. Bail, B. Guay, E. Maloney, A. Combs, D. S. Hillygus, F. Merhout, D. Freelon, and A. Volfovsky · 2020
Later among the works it cites.
Networks beyond pairwise interactions: structure and dynamics
F. Battiston, G. Cencetti, I. Iacopini, V. Latora, M. Lucas, A. Patania, J.-G. Young, and G. Petri · 2020
Later among the works it cites.
Annotated hypergraphs: models and applications
P. Chodrow and A. Mellor · 2020
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A web-based collaborative annotation and consolidation tool
T. Daudert · 2020
Later among the works it cites.
Unraveling the origin of social bursts in collective attention
M. De Domenico and E. G. Altmann · 2020
Later among the works it cites.
Black trolls matter: Racial and ideological asymmetries in social media disinformation
D. Freelon, M. Bossetta, C. Wells, J. Lukito, Y. Xia, and K. Adams · 2020
Later among the works it cites.
Assessing the risks of ‘infodemics’ in response to covid-19 epidemics
R. Gallotti, F. Valle, N. Castaldo, P. Sacco, and M. De Domenico · 2020
Later among the works it cites.
A random growth model with any real or theoretical degree distribution
F. Giroire, S. Pérennes, and T. Trolliet · 2020
Later among the works it cites.
The Future of False Information Detection on Social Media: New Perspectives and Trends
B. Guo, Y. Ding, L. Yao, Y. Liang, and Z. Yu · 2020
Later among the works it cites.
MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis
D. Hazarika, R. Zimmermann, and S. Poria · 2020
Later among the works it cites.
Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement
L. Hébert-Dufresne, S. V. Scarpino, and J.-G. Young · 2020
Later among the works it cites.
Modeling complex spatial patterns with temporal features via heterogenous graph embedding networks
Y. Huang, H. Xu, Z. Duan, A. Ren, J. Feng, Q. Zhang, and X. Wang · 2020
Later among the works it cites.
Rose: Role-based signed network embedding
A. Javari, T. Derr, P. Esmailian, J. Tang, and K. C.-C. Chang · 2020
Later among the works it cites.
Semantically modeling cyber influence campaigns (cics): Ontology model and case studies
N. Johnson, B. Turnbull, T. Maher, and M. Reisslein · 2020
Later among the works it cites.
Community detection algorithm using hypergraph modularity
B. Kamiński, P. Prałat, and F. Théberge · 2020
Later among the works it cites.
An unsupervised framework for comparing graph embeddings
B. Kamiński, P. Prałat, and F. Théberge · 2020
Later among the works it cites.
Hypergraph clustering by iteratively reweighted modularity maximization
T. Kumar, S. Vaidyanathan, H. Ananthapadmanabhan, S. Parthasarathy, and B. Ravindran · 2020
Later among the works it cites.
FNED: A Deep Network for Fake News Early Detection on Social Media
Y. Liu and Y.-F. B. Wu · 2020
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Grace: Gradient harmonized and cascaded labeling for aspect-based sentiment analysis, 2020
H. Luo, L. Ji, T. Li, N. Duan, and D. Jiang · 2020
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FANG: Leveraging Social Context for Fake News Detection Using Graph Representation
V.-H. Nguyen, K. Sugiyama, P. Nakov, and M.-Y. Kan · 2020
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Fraud detection: A systematic literature review of graph-based anomaly detection approaches
T. Pourhabibi, K.-L. Ong, B. H. Kam, and Y. L. Boo · 2020
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What you feel, is what you like influence of message appeals on customer engagement on instagram
R. Rietveld, W. van Dolen, M. Mazloom, and M. Worring · 2020
Later among the works it cites.
Parameterized objectives and algorithms for clustering bipartite graphs and hypergraphs
N. Veldt, A. Wirth, and D. F. Gleich · 2020
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TransModality: An End2End Fusion Method with Transformer for Multimodal Sentiment Analysis
Z. Wang, Z. Wan, and X. Wan · 2020
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A comprehensive survey on graph neural networks
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and S. Y. Philip · 2020
Later among the works it cites.
Graph neural networks: A review of methods and applications
J. Zhou, G. Cui, S. Hu, Z. Zhang, C. Yang, Z. Liu, L. Wang, C. Li, and M. Sun · 2020
Later among the works it cites.
Fake News Early Detection: A Theory-driven Model
X. Zhou, A. Jain, V. V. Phoha, and R. Zafarani · 2020
Later among the works it cites.
Persistent Anti-Muslim Bias in Large Language Models
A. Abid, M. Farooqi, and J. Zou · 2021
Closest in time.
A survey on sentiment analysis and opinion mining in greek social media
G. Alexandridis, I. Varlamis, K. Korovesis, G. Caridakis, and P. Tsantilas · 2021
Closest in time.
A survey of twitter research: Data model, graph structure, sentiment analysis and attacks
D. Antonakaki, P. Fragopoulou, and S. Ioannidis · 2021
Closest in time.
An Overview of Fairness in Data – Illuminating the Bias in Data Pipeline
S. K. B, A. Chandrabose, and B. R. Chakravarthi · 2021
Closest in time.
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
E. M. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell · 2021
Closest in time.
Network geometry
M. Boguna, I. Bonamassa, M. De Domenico, S. Havlin, D. Krioukov, and M. Á. Serrano · 2021
Closest in time.
From symbols to embeddings: A tale of two representations in computational social science
H. Chen, C. Yang, X. Zhang, Z. Liu, M. Sun, and J. Jin · 2021
Closest in time.
Detecting Hate Speech with GPT-3
K.-L. Chiu and R. Alexander · 2021
Closest in time.
Incorporating symbolic domain knowledge into graph neural networks
T. Dash, A. Srinivasan, and L. Vig · 2021
Closest in time.
Evaluating node embeddings of complex networks
A. Dehghan-Kooshkghazi, B. Kamiński, L. Kraiński, P. Prałat, and F. Théberge · 2021
Closest in time.
Bots are less central than verified accounts during contentious political events
S. González-Bailón and M. De Domenico · 2021
Closest in time.
A multi-purposed unsupervised framework for comparing embeddings of undirected and directed graphs
B. Kamiński, Ł. Kraiński, P. Prałat, and F. Théberge · 2021
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Artificial benchmark for community detection (abcd): Fast random graph model with community structure
B. Kamiński, P. Prałat, and F. Théberge · 2021
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How True is GPT-2? An Empirical Analysis of Intersectional Occupational Biases
H. Kirk, Y. Jun, H. Iqbal, E. Benussi, F. Volpin, F. A. Dreyer, A. Shtedritski, and Y. M. Asano · 2021
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SNAP Datasets: Stanford large network dataset collection
J. Leskovec and A. Krevl · 2021
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How does homophily shape the topology of a dynamic network?
X. Li, M. Mobilia, A. M. Rucklidge, and R. Zia · 2021
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What Makes Good In-Context Examples for GPT-$3$?
J. Liu, D. Shen, Y. Zhang, B. Dolan, L. Carin, and W. Chen · 2021
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Whom to trust in a signed network? optimal solution and two heuristic rules
F. Meng, M. Medo, and B. Buechel · 2021
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Language Models have a Moral Dimension
P. Schramowski, C. Turan, N. Andersen, C. Rothkopf, and K. Kersting · 2021
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Reddit’s self-organised bull runs: Social contagion and asset prices
V. Semenova and J. Winkler · 2021
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Hyperbolic node embedding for signed networks
W. Song, H. Chen, X. Liu, H. Jiang, and S. Wang · 2021
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Hgcf: Hyperbolic graph convolution networks for collaborative filtering
J. Sun, Z. Cheng, S. Zuberi, F. Perez, and M. Volkovs · 2021
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Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models
A. Tamkin, M. Brundage, J. Clark, and D. Ganguli · 2021
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Community detection in networks using graph embeddings
A. Tandon, A. Albeshri, V. Thayananthan, W. Alhalabi, F. Radicchi, and S. Fortunato · 2021
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A survey on federated learning
C. Zhang, Y. Xie, H. Bai, B. Yu, W. Li, and Y. Gao · 2021
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Systematic comparison of graph embedding methods in practical tasks
Y.-J. Zhang, K.-C. Yang, and F. Radicchi · 2021
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Calibrate Before Use: Improving Few-Shot Performance of Language Models
T. Z. Zhao, E. Wallace, S. Feng, D. Klein, and S. Singh · 2021
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