Twitter is one of the most popular social network. Daily tweets on the widest variety of topics reflect not only the interest but the influence of the users within the community. These tweets are often liked or retweeted by other users showing their relative popularity.

In this data visualization project the timeline of most recent tweets on Climate Change is shown. Each of the circles display the total amount of activity including likes and retweets. Only the top ten are explicitly displayed in this dataviz.


This project has used the Twitter API for data retrieval based on the hashtag #ClimateChange, recovering the last 600 tweets. The retrieval has been done using Tweepy in Python. Additional postprocessing of text and stats has been done in Pandas.

Data has been stored in a MySQL Database and accessed through SQL requests via PHP. The data visualization part has been developed using D3.js and framed in HTML and CSS.