# Automatic Monitoring Social Dynamics During Big Incidences: A Case Study of COVID-19 in Bangladesh

arXiv: https://arxiv.org/abs/2101.09667 · HTML: https://mlsanity.com/paper/2101.09667/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 49 references that are in the map.
- First posted on arXiv 24 Jan 2021.

## Builds on (most cited first, 11 of 11)

- [The Dynamic Embedded Topic Model](https://mlsanity.com/paper/1907.05545/) (2019)
- [QutNocturnal@HASOC'19: CNN for Hate Speech and Offensive Content Identification in Hindi Language](https://mlsanity.com/paper/2008.12448/) (2020)
- [Sentiment Analysis on Bangla and Romanized Bangla Text (BRBT) using Deep Recurrent models](https://mlsanity.com/paper/1610.00369/) (2016)
- [Machine learning approach for text and document mining](https://mlsanity.com/paper/1406.1580/) (2014)
- [Supervised learning Methods for Bangla Web Document Categorization](https://mlsanity.com/paper/1410.2045/) (2014)
- [Misogynistic Tweet Detection: Modelling CNN with Small Datasets](https://mlsanity.com/paper/2008.12452/) (2020)
- [Understanding the Spatio-temporal Topic Dynamics of Covid-19 using Nonnegative Tensor Factorization: A Case Study](https://mlsanity.com/paper/2009.09253/) (2020)
- [Automatic classification of bengali sentences based on sense definitions present in bengali wordnet](https://mlsanity.com/paper/1508.01349/) (2015)
- [A Comparative Study on Different Types of Approaches to Bengali document Categorization](https://mlsanity.com/paper/1701.08694/) (2017)
- [Topic modelling discourse dynamics in historical newspapers](https://mlsanity.com/paper/2011.10428/) (2020)
- [Topic, Sentiment and Impact Analysis: COVID19 Information Seeking on Social Media](https://mlsanity.com/paper/2008.12435/) (2020)

## Abstract (arXiv)

Newspapers are trustworthy media where people get the most reliable and credible information compared with other sources. On the other hand, social media often spread rumors and misleading news to get more traffic and attention. Careful characterization, evaluation, and interpretation of newspaper data can provide insight into intrigue and passionate social issues to monitor any big social incidence. This study analyzed a large set of spatio-temporal Bangladeshi newspaper data related to the COVID-19 pandemic. The methodology included volume analysis, topic analysis, automated classification, and sentiment analysis of news articles to get insight into the COVID-19 pandemic in different sectors and regions in Bangladesh over a period of time. This analysis will help the government and other organizations to figure out the challenges that have arisen in society due to this pandemic, what steps should be taken immediately and in the post-pandemic period, how the government and its allies can come together to address the crisis in the future, keeping these problems in mind.