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.
翻译:以大赦国际为基础的研究主要围绕一个特定事件调查难民问题,并考虑采用单一方式方法。相反,我们采用了一个多式联运结构来调查难民从家乡到东道国的旅程。我们从Arnold van Genneep的人类学工作“Les Rites de Passage”中汲取了深刻的见解,人类学工作系统地分析一个人从一个群体或社会向另一个群体或社会过渡的情况。根据Genneep的分离-过渡-融合框架,我们确定了难民旅程的四个阶段:难民抵达、在庇护地暂时停留、康复和难民融入东道国。我们从2020年4月至2021年3月收集了0.23万个多式推文,用于测试这一拟议的框架工作。我们发现,基于变异语言模式和最新图像识别模型的结合,如BERT+LSTM和IncepionV4的融合,可以超越一个模式。随后,检验我们提议的模式在现实时期的实际影响:难民的停留在庇护、康复和难民融入到东道国的融合。我们从2020年4月收集了0.22万条多式推文框架,我们考虑了这个2022万福德危机的总框架。