Having understood in which of the two queries people are more active we examined these deeper to comprehend how Youtube video producers andusers behave according to the language, category and the type of video. It seemed interesting to show the differences between those who uploaded videos and who viewed them.
We chose the Sunburst as type of graphic. All three graphs are cut in halves to represent simultaneously the results of the query Deep Web (purple) and those for Tor Browser (green). Each of these halves is further cut into slices whose size is the amount of video and the height of which is the appreciation index. So that you can see for example what is the highest amount of video type presents and what is the most appreciated by users. In some cases this two information do not coincide. So that we can say that the graphs show two levels of comparison: one that could be considered external made of the different behavior of the two queries, and an internal made of types, languages and categories of the single query.
Through the function "Sum" of Excel and the use of the filters, we calculated the number of videos by typology, Youtube category and language of both queries. So that we delineated the chart thanks to the tool Raw. Using the visual representation typology sunburst we had a double ring: one outside where we placed respectively video typology, Youtube category and video languages and one inside where we placed the two analyzed queries. Furthermore, the program itself has divided the external ring into slices whose width expresses the amount of video typology, language and Youtube category.
In another Excel file the ratio between the amount of video typology, language, Youtube category was calculated and we crossed these values with those related to the activity index. The activity index is an index that we have created ad hoc thanks to the function: [* 1 views + 50 * (+ Like Dislike) + 250 * Comments]. During the first analysis we realized that using this index it was possible to get information on Youtube behavior users.
Later we changed all the “sunburst” slices, previously created, to add data related to the activity index and with the use of an additional text we were able to transmit detailed data of the differences that seemed important to emphasize.
The graphs show the differences in behavior between the amount of videos by category, type, language and those in which there is an increased activity and participation by users. For example the most uploaded type of video in both queries is tutorial but those with an highest index of activity are: for the Deep Web Talk and for Tor Browser is VLOG. This difference does not appear in the language graph, in which generally the highest amount of video are also the most viewed. In the categories graph we can see a difference in Tor Browser graph where News and Politic, despite being a category with the minor amounts of video in proportion to the others, it is one of the most active. Furthermore, the graph allows us to have a good overview of the two queries for the selected variables. For example we can see how the Deep Web has much more types than Tor Browser because the first one is more argumentative instead Tor Browser is made of video like tutorials incident to technology. Users generally show information and education on the topic and on the differences between these terms and their corresponding meanings.
