Disinformation Visualization: How to lie with datavis

By Mushon Zer-Aviv, January 31, 2014 Seeing is believing. When working with raw data we’re often encouraged to present it differently, to give it a form, to map it or visualize it. It all sounds very sinister, and indeed sometimes it is. Over the past year I’ve had a few opportunities to run Disinformation Visualization workshops, encouraging activists, designers, statisticians, analysts, researchers, technologists and artists to visualize lies. Centuries before big data, computer graphics and social media collided and gave us the datavis explosion, visualization was mostly a scientific tool for inquiry and documentation. Reproducing Lies Let’s set up some rules. We don’t spread visual lies by presenting false data. To deconstruct possible lies I suggest we use the content / structure / presentation model as three lenses through which we can analyse a graphic. Should we legalize the killing of babies? I would hope most of you would say: No. Should women have the right to their own bodies?

7 tools for scraping - Use for datajournalism & insightful content I’ve been creating a lot of (data driven) creative content lately and one of the things I like to do is gathering as much data as I can from public sources. I even have some cases it is costing to much time to create and run database queries and my personal build PHP scraper is faster so I just wanted to share some tools that could be helpful. Just a short disclaimer: use these tools on your own risk! 1. Scraper is a simple data mining extension for Google Chrome™ that is useful for online research when you need to quickly analyze data in spreadsheet form. You can select a specific data point, a price, a rating etc and then use your browser menu: click Scrape Similar and you will get multiple options to export or copy your data to Excel or Google Docs. 2. – Click here to download the example script. 3. 4. 5. 6. 7. But on the end, building your individual project scrapers will always be more effective than using predefined scrapers. Summary Article Name Author Jan-Willem Bobbink Description

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