Local Chapter EAFIT University, Colombia Chapter
Status: Completed
Project Duration: 14 Aug 2021 - 14 Sep 2021
Open Source resources available from this project
Project background.
The recent national strike in Colombia arose from the need of the different social sectors of the country to demonstrate their discontent with the current government. Some of the disconformities include the presentation of tax and health reforms, the increase in unemployment and the growth of violence, and the violation of human rights, among others. From the beginning of the strike as of June 15, 2021, the Colombian government has reported more than 6,937 rallies, 2,410 marches, 3,440 blockades, 669 mobilizations, and 34 assemblies, and total losses range between COP 11.8 and 12 billion (approximately USD 3,000 million). Most of these issues are commented on social networks such as Facebook or Twitter, where people share their ideas and perceptions, but false information is also shared, which generates disinformation.
The problem.
The objective of the project is to identify these insights, perspectives, sentiments and fake news on Colombia’s national strike on social networks using natural language processing (NLP) or other artificial intelligence techniques to get a much better understanding of what is happening.
The identification of these insights and perspectives may allow the main stakeholders to learn first-hand what is being said about the strike in social networks and identify ideas for resolving the disagreement between the parties. In addition, it is very important to inform people in a simple and truthful way about what is happening in the country with the national strike or with other social problems as well.
The main idea is that people who are in digital environments from which they receive information on a daily basis are able to use and receive the benefits contained in this challenge. Also, this project can be adapted to future social unrest.
Project goals.
Goals:
- Perform web scraping to extract information from social networks.
- Build an NLP model that identifies the opinions, perspectives, and sentiments of people in social networks. This will allow us to observe differences between social networks.
- Summarize the opinions on each topic in the context of the national strike through a dashboard to better understand the issues.
Project plan.
Learning outcomes.
1. Ability to perform data extraction through Web Scraping in different social networks.
2. To know how to make an NLP model that identifies insights and perspectives about the national strike in Colombia in social networks.
3. To be able to build a dashboard that synthesizes information about the national strike.
