Description
In this section we want to see in which categories of websites, gender equality
and gender inequality are mostly discussed. For our research starting point we decided to look at Google as it is an accessible and popular platform that provides an abundant source of information.
Starting from both of our queries, we discovered that 'gender inequality' is mostly mentioned in News and Media and Education websites, whereas for 'gender equality' Government and Legal is the category of websites where the query is debated more. Therefore, among the Government and Legal websites there are many organizations such as Unesco, Unwomen and Ilo whose main goal is working towards achieving equality between the genders. 'Gender inequality' is mentioned more in News and Media because these kind of websites report mostly about steps forward or regression in gender equality and injustices that people experience.
Protocol
In order to avoid google personalization we used google.com/ncr in incognito mode and searched for two different phrases: “Gender Inequality” and “Gender Equality”. We chose not to set up a time range for the research because we want the results to be more similar to the real world user, searching for the topic on Google. Then we manually excluded Google Books and Wikipedia pages, taking the first 100 results for each search.
To have a better understanding of the differences of the results of each query, we categorized each link that came up, using Webpulse Site Review. So we found out that websites appearing under “Gender Equality” query are mostly categorized as News and Media (32.2%) and Education (20.7%) while “Gender Inequality” is mostly categorized under Government and Legal (28%) and News and Media (19.04%) At this point we were able to see that the input terminology has a definite effect on the results that are then output.
Data
Timestamp: 01/12/2016 - 05/12/2016
Data source: Scopus, Google Scholar
Download data (4MB)
Our dataset consists of a table in which we have categories and the number of article for each of them. Then we have also calculated in a third column the percentage of how many times each category occur.