Decoding Multilingual Topic Dynamics and Trend Identification through ARIMA Time Series Analysis on Social Networks: A Novel Data Translation Framework Enhanced by LDA/HDP Models

arXiv:2403.15445v1 Announce Type: cross
Abstract: In this study, the authors present a novel methodology adept at decoding multilingual topic dynamics and identifying communication trends during crises. We focus on dialogues within Tunisian social networks during the Coronavirus Pandemic and other notable themes like sports and politics. We start by aggregating a varied multilingual corpus of comments relevant to these subjects. This dataset undergoes rigorous refinement during data preprocessing. We then introduce our No-English-to-English Machine Translation approach to handle linguistic differences. …

abstract adept analysis arima arxiv authors communication cs.ai cs.cl cs.lg cs.si data decoding dynamics focus framework identification lda methodology multilingual networks novel series social social networks study through time series translation trend trends type