Description

The research of images on Google was done to verify how different media represent the IS in terms of visual content. The research queries were selected in order to compare different sources: (i) “ISIS” on Google images in general; (ii) “ISIS + foreign fighters” from the previous research phase; (iii) “ISIS + Allah”, “ISIS + people”, “ISIS + Sham + Iraq” are the most recurrent words in the official magazines Dabiq and Rumiyah; (iv) “ISIS + Sham + Iraq”, “ISIS + jihadist”, “ISIS + Mosul” are the words where the controversy is focused on Wikipedia based on how many times those words were changed; (v) “ISIS on telegraph.co.uk”, “ISIS on euronews.com”, “ISIS on mirror.co.uk”, “ISIS on bbc.co.uk” to filter results by european media as analyzed for news articles; (vi) “ISIS on youtube.com” to include the image given by a media largerly used for the communication of the IS on the web.

The analysis of the images with Clarifai APIs allowed to assign color models via machine learning. The comparison of the distribution of the colors per every query permits to locate the similarities and the differences between the images resulting from all the queries. The visualization shows all the color models extracted by Clarifai ordered per HEX value. It’s very apparent that all the queries share basically the same colors, moreover with the same density distribution. Hence the visual communication by the media offers a strong and homogeneous image, even though the images resulting for each query are different, yet similar. By clicking on the query name or the color models, the user can access all the corresponding images.

Protocol

For every query, a research on images.google.com was done. With the Google Chrome extension “Faktun Batch”, the first 20 image results for every query were downloaded. For the query “ISIS + foreign fighters”, 60 images were initially collected because for a big part they were maps of analysis carried out by third parties. Of the initial corpus of 280 images, 255 were selected by deleting those not pertinent to the research; for the query “ISIS + foreign fighters”, only the first 20 images were kept of the resulting 40 after cleansing. In order to access the Clarifai API, the URLs for every image were needed. All the images were uploaded in query-structured folders on GitHub and with the Google Chrome extension Web Scraper all the raw URLs were collected into an excel file. The URLs were then used in batches of 20 on Clarifai to extract color models. The resulting JSON files were mounted into one excel file using OpenRefine. Color models and color density were visualized using NodeBox.

Data

Timestamp: 07/12/2016 - 11/12/2016

Data source: Clarifai

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The dataset has one column that identifies the query, one column contains the URLs of the images, hence the images file names for identification, and columns for hex color codes, w3c hex color codes, w3c color names, and finally the color density. The dataset has a single page dedicated per each query and one page with all the data listed together.