The UNHCR, the UN Refugee Agency, is a global organization dedicated to saving lives, protecting rights and building a better future for refugees, forcibly displaced communities and stateless people. In response to the current global refugee crisis, a special projects unit called The Hive was recently formed to find creative ways of addressing the global refugee crisis, specifically focusing on American engagement with refugee issues. A critical aspect to The Hive's mission is tracking engagement amongst Americans with regards to refugee-related issues.
Thus, your project will be to develop a social listening tool that can take all the social media activity (on Facebook, Twitter, and Instagram) related to refugees specifically and aggregates the data in such a way that provides us with a clear picture about the current state of American engagement regarding refugee issues.
Let's get to work.
Level 1: Your baseline deliverable will be to create a social media aggregator that listens to social media networks (specifically Twitter, Facebook, and Instagram), parsing user content related to refugee-issues and turning that into a feed. We recommend doing this in the form of an HTML web application, but we are flexible regarding the final platform as long as you do the necessary prototyping/research to justify your design choices.
Level 2: Additionally, the tool should display information in such a way that the Hive can determine the general sentiment towards refugees in a certain city/area. Refer to general sentiment ranking techniques used in NLP to do this.
Also, allow the user to filter refugee sentiment by demographic variables (such as age, gender, income, education, congressional district, etc…) using publicly available data sources.
Level 3: Implement a stunning data visualization that displays statistics on refugee support by state using Tableau. The visualization should implement the sentiment extraction tool you previosly created. Feel free to expand this visualization to account for other factors too, such as the demographic factors you took into account in Level 2.