With this visualization we would like to explore in more depth one of the pattern we found during the section 2 of our research. We observed that almost all the videos categorized as “other”, were characterized by a common theme: the fake. In these videos, different users report their theory about the alleged falsification of the execution’s videos. Each bar represents a video whose eight depends on the amount of visualization obtained by the video and whose color indicates the source of the video. The lines connect the video with their arguments. Above the bars, two squares show through the dimension the amount of comments obtained by the video e through the color the division between who agree with the theory and who disagree.

It is quite clear a majority of the theories that show staging evidence of the executions, followed by those that show a replacement of the hostage and those that individuate post-production evidences. The pro and cons amount of comments are almost the same most of the time.


excel corpus definition YTDT video+info comments chrome extention scraper open refine excel illustrator visualization comments extractionfrom +18 videos 1. from DATABASE 2— selecting "other" videos— detecting "fake videos" file tab extraction from tab to csv from DATABASE 2 creating DATABASE 7 containing5 Spreadsheets1. General informations— ranking— query— site domain— site typology— censorship level— notes— url— video typology— n. views— n. comments— fake theories2,3,4,5. Video comments— ranking— polarization— comments HOW TO READ: website terminal software tool corpusdefinition visualization networkdefinition data-sourcedefinition queriesdefinition
1. Corpus definition

This step started from the video-dataset 2. In particular, we analyzed the “other” video category, and we detected the “fake videos”. We extracted the comments using Chrome Extension Scraper for +18 videos and YTDT video+ info comments, for youtube videos. The output were respectively a text and TAB file. The tab was converted in CSV using Open Refine. We created a Excel file with all the information we got from the videos such as, visualizations, comments, topics of the video and of the comments.


Timestamp: 12/12/2016 – 19/12/20

Data source: Google video

To create this .xls we selected the ‘other’ type videos and we identified the Fake ones. The first spreadsheet contains the original columns from DATABASE 2. We added a spreadsheet per event with fake videos with 3 more columns about: rank, polarization about video’s theory (pro/cons) and comments texts.