mlsanityData to 14 Oct 2026

Community Learning: Understanding A Community Through NLP for Positive Impact

arXiv 2210.00590 ↗First posted 2 Oct 2022cs.CLcited by 0

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Abstract (arXiv)

A post-pandemic world resulted in economic upheaval, particularly for the cities' communities. While significant work in NLP4PI focuses on national and international events, there is a gap in bringing such state-of-the-art methods into the community development field. In order to help with community development, we must learn about the communities we develop. To that end, we propose the task of community learning as a computational task of extracting natural language data about the community, transforming and loading it into a suitable knowledge graph structure for further downstream applications. We study two particular cases of homelessness and education in showing the visualization capabilities of a knowledge graph, and also discuss other usefulness such a model can provide.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 48 references that are in the map. First posted on arXiv 2 Oct 2022.

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12 of 48 references.

References · 12

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  2. 2020A Survey on Knowledge Graphs: Representation, Acquisition and Applicationscited by 643
  3. 2020LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attentioncited by 326
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  8. 2019SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networkscited by 7
  9. 2021Empathy and Hope: Resource Transfer to Model Inter-country Social Media Dynamicscited by 4
  10. 2019Scalable Knowledge Graph Construction from Twittercited by 1
  11. 2021Semantic Foundations of Seraph Continuous Graph Query Languagecited by 1
  12. 2022LotRec: A Recommender for Urban Vacant Lot Conversioncited by 1

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