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This was a project completed as part of the Inter-University Big Data Challenge in 2021. The team of 4 used network analysis, regression and dimensionality reduction techniques to predict the veracity of tweets

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UG-Data-Challenge-2021

This was a project completed as part of the Inter-University Big Data Challenge in 2021. The team of 4 used network analysis, regression and dimensionality reduction techniques to predict the veracity of tweets. We used text feature extraction to obtain the final datasets for the analysis. We were first place (among 100 teams from 39 universities), and were awarded the Overleaf Outstanding Science communication award. Our work was published in STEM Fellowship Journal. We used tools like Python, sklearn, OpenOrd, scipy and COVAiD DB for this analysis.

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Overall competition description where our names and project onformation can be found: https://www.stemfellowship.org/case-study/national-inter-university-big-data-challenge-2021/ Full Manuscript: https://drive.google.com/file/d/1Gcn6M--Tuux-_HxfGHaQ62rcw4GyrT68/view Video of Project: https://www.youtube.com/watch?v=CpYXWYto7YY DOI link for our research. https://journal.stemfellowship.org/doi/abs/10.17975/sfj-2021-003 PDF link for our research : https://journal.stemfellowship.org/doi/pdf/10.17975/sfj-2021-003

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This was a project completed as part of the Inter-University Big Data Challenge in 2021. The team of 4 used network analysis, regression and dimensionality reduction techniques to predict the veracity of tweets

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