Rites de Passage: Elucidating Displacement to Emplacement of Refugees on Twitter
Not on the map. Why?
Abstract (arXiv)
Social media deliberations allow to explore refugee-related is-sues. AI-based studies have investigated refugee issues mostly around a specific event and considered unimodal approaches. Contrarily, we have employed a multimodal architecture for probing the refugee journeys from their home to host nations. We draw insights from Arnold van Gennep's anthropological work 'Les Rites de Passage', which systematically analyzed an individual's transition from one group or society to another. Based on Gennep's separation-transition-incorporation framework, we have identified four phases of refugee journeys: Arrival of Refugees, Temporal stay at Asylums, Rehabilitation, and Integration of Refugees into the host nation. We collected 0.23 million multimodal tweets from April 2020 to March 2021 for testing this proposed frame-work. We find that a combination of transformer-based language models and state-of-the-art image recognition models, such as fusion of BERT+LSTM and InceptionV4, can out-perform unimodal models. Subsequently, to test the practical implication of our proposed model in real-time, we have considered 0.01 million multimodal tweets related to the 2022 Ukrainian refugee crisis. An F1-score of 71.88 % for this 2022 crisis confirms the generalizability of our proposed framework.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 61 references that are in the map. First posted on arXiv 30 May 2022.
Builds on
14 of 61 references.
References · 14
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
- 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
- 2016Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learningcited by 1,512
- 2017Multimodal Machine Learning: A Survey and Taxonomycited by 1,013
- 2020The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memescited by 490
- 2020Deep Learning Based Text Classification: A Comprehensive Reviewcited by 141
- 2018CrisisMMD: Multimodal Twitter Datasets from Natural Disasterscited by 89
- 2019Automatic detection of passable roads after floods in remote sensed and social media datacited by 6
- 2018Multimodal Social Media Analysis for Gang Violence Preventioncited by 5
Built on by
Not cited yet.