research question

Is there a relationship between the search index for nuclear reactors and their location?

Description

Analysing the trend of the research we wanted to see if the interest in nuclear reactors for these two countries was related to their location.

The search engines Google and Baidu, respectively for USA and China, were taken to focus on our research and see where the general query "Nuclear Reactor" was most researched.

We decided also to compare the ranking result for every country and province with the population. The result is that in China the most populated provinces search most for nuclear reactor and they are also provinces with the highest number of reactors on it. Otherwise in USA the most populated countries don’t search much for reactors and the countries that actually have reactors operating are more distributed than the chinese analysis.

Protocol

The aim of this question was to investigate if the interest of nuclear reactors was most in the regions where actually the reactors are located or in areas far away from nuclear reactors.

With the query “Nuclear Reactor” for Google Trends and “核电站”(Nuclear Reactor) for Baidu Index, the research was conducted from 2016 (after Paris Climate Change Agreement) until November 2017, both for China and USA.

Data

Data source: Google Trends , Baidu Index
                         USA Power Plants , China Power Plants
                         USA Country list Population , China Provinces Population

Google Trends and Baidu Index let you download data about the location of the online researches related to a given query.

We collected the data from this to websites. Google Trends and Baidu Index doesn’t have the same values of visualization for the location. One is made by average of researches and one by a research ranking. We decided to transform the Google Trends data into ranking to make it compatible with Baidu Index.

We also decided to compare the data from the two websites with the exact location of the nuclear reactors and the countries population. We took this data from wikipedia and we visualized it.