mlsanityData to 7 Oct 2026

Socially Enhanced Situation Awareness from Microblogs using Artificial Intelligence: A Survey

arXiv 2209.07272 ↗First posted 13 Sep 2022cs.LGcited by 5

Not on the map. Why?

Abstract (arXiv)

The rise of social media platforms provides an unbounded, infinitely rich source of aggregate knowledge of the world around us, both historic and real-time, from a human perspective. The greatest challenge we face is how to process and understand this raw and unstructured data, go beyond individual observations and see the "big picture"--the domain of Situation Awareness. We provide an extensive survey of Artificial Intelligence research, focusing on microblog social media data with applications to Situation Awareness, that gives the seminal work and state-of-the-art approaches across six thematic areas: Crime, Disasters, Finance, Physical Environment, Politics, and Health and Population. We provide a novel, unified methodological perspective, identify key results and challenges, and present ongoing research directions.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 40 of its 179 references that are in the map. First posted on arXiv 13 Sep 2022.

Builds on

40 of 179 references.

References · 40

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  5. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  6. 2022Generative Adversarial Networkscited by 5,603
  7. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  8. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  9. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
  10. 2018Deep contextualized word representationscited by 2,285
  11. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  12. 2018Graph Neural Networks: A Review of Methods and Applicationscited by 1,571
28 more
  1. 2014How transferable are features in deep neural networks?cited by 1,216
  2. 2019A Comprehensive Survey on Transfer Learningcited by 1,154
  3. 2021Scaling Vision Transformerscited by 993
  4. 2019Data-Efficient Image Recognition with Contrastive Predictive Codingcited by 672
  5. 2019Self-supervised Visual Feature Learning with Deep Neural Networks: A Surveycited by 656
  6. 2021CoAtNet: Marrying Convolution and Attention for All Data Sizescited by 566
  7. 2018Do Better ImageNet Models Transfer Better?cited by 560
  8. 2019Generalizing from a Few Examples: A Survey on Few-Shot Learningcited by 462
  9. 2017Representation Learning on Graphs: Methods and Applicationscited by 456
  10. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
  11. 2019SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimizationcited by 253
  12. 2020Machine Learning on Graphs: A Model and Comprehensive Taxonomycited by 156
  13. 2020Better Fine-Tuning by Reducing Representational Collapsecited by 156
  14. 2020Named Entity Recognition as Dependency Parsingcited by 150
  15. 2017Learned in Translation: Contextualized Word Vectorscited by 104
  16. 2017Detection and Resolution of Rumours in Social Media: A Surveycited by 103
  17. 2021Supporting Clustering with Contrastive Learningcited by 90
  18. 2014Processing Social Media Messages in Mass Emergency: A Surveycited by 50
  19. 2018False Information on Web and Social Media: A Surveycited by 33
  20. 2020Neural Topic Modeling with Bidirectional Adversarial Trainingcited by 29
  21. 2019Location reference identification from tweets during emergencies: A deep learning approachcited by 14
  22. 2018A Twitter Tale of Three Hurricanes: Harvey, Irma, and Mariacited by 12
  23. 2019Keyphrase Extraction from Disaster-related Tweetscited by 12
  24. 2020From Twitter to Traffic Predictor: Next-Day Morning Traffic Prediction Using Social Media Datacited by 10
  25. 2019Twitter Speaks: A Case of National Disaster Situational Awarenesscited by 9
  26. 2015140 Characters to Victory?: Using Twitter to Predict the UK 2015 General Electioncited by 6
  27. 2018Twitter for Sparking a Movement, Reddit for Sharing the Moment: #metoo through the Lens of Social Mediacited by 6
  28. 2017Intelligent Disaster Response via Social Media Analysis - A Surveycited by 2

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 1.

5 papers.

  1. 2023CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media textscited by 7
  2. 2022Where did you tweet from? Inferring the origin locations of tweets based on contextual informationcited by 6
  3. 2024CReMa: Crisis Response through Computational Identification and Matching of Cross-Lingual Requests and Offers Shared on Social Mediacited by 4
  4. 2024Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Textscited by 1
  5. 2025"Actionable Help" in Crises: A Novel Dataset and Resource-Efficient Models for Identifying Request and Offer Social Media Postscited by 0