On Facebook, Twitter, and pretty much every social media platform, there are trending topics. However, there lacks the emotions to reflect such topics. One example is the hurricane about to strike Florida; we assumed that the region would be rather distressed and that such distress would be displayed throughout Florida news. This brought to our attention Google's natural language sentiment analyzer API and we wanted to find a means of associating emotions with all regions of the world.

What it does

Moody Maps displays how different regions of the world feel about a certain topic using emoticons. By searching a keyword, we analyze the trending news articles on the searched keyword and associate the trends with a mood on our google map interface. Our primary features include: • Keyword search • Real-time news analysis • Timeline range selector

Challenges we ran into

• Combining circle visualization with markers in Google Map's API. • Scrape the first image off search engine for article titles. • Penn flagged our domain as malware so we couldn't redirect it to the correct IP address for our server. • We had to create an asynchronous backend in order to display media while simultaneously update the map

Accomplishments that we're proud of

Creating a unique way to view moods around the world. We found out Moscow has positive joyful sentiments towards Donald Trump while the rest of the world has fearful and angry sentiments.

What we learned

How to use APIs, javascript, python

What's next for Moody Maps

Circle visualization on map based on sentiment and number of related articles found for each trending region.

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