  Third world countries tend to have a higher share of plastic waste that is
inadequately managed while the First world countries have higher plastic waste
generation per person. A difference in the characteristics of plastic pollution
depending on the country's standing results in varying optimal recommendations
for users. Through Big Text and OSOME meme analysis, I constructed a list with
optimal recommendations for First World and Third World countries. Based on the
list, I designed a User Interface wit Google Apps Scripts that provide
personalized recommendations based on the country's standing and user's
preferred difficulty and reassessed the code based on the six qualities of
code. The purpose of the User Interface is to aid people who wish to help solve
plastic pollution by offering a set of personalized tasks for each user and
keeping their progress accountable through a point tracking system. With a
significant number of users, the application could eventually contribute to
solving the problem of plastic pollution.
