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This toolkit is provided by the InVID european project to help journalists to verify content on social networks (please note that external InVID services used via this interface, such as those presented under the Analysis and Keyframes tabs, are not open-sourced). It has been designed as a verification “Swiss army knife” helping journalists to save time and be more efficient in their fact-checking and debunking tasks on social networks especially when verifying videos and images.
The provided tools allow you to quickly get contextual information on Facebook and YouTube videos, to perform reverse image search on Google, Baidu or Yandex search engines, to fragment videos from various platforms (Facebook, Instagram, YouTube, Twitter, Daily Motion) into keyframes, to enhance and explore keyframes and images through a magnifying lens, to query Twitter more efficiently through time intervals and many other filters, to read video and image metadata, and to apply forensic filters on still images. The main features of the toolkit are explained below, and in the following tutorial video.
This is a new feature (supported in v0.59) to access the InVID plugin and to help journalists to retrieve video and image URLs within the code of a web page. After clicking on the InVID plugin button of the browser menu, the user is showed the following menu.
Below, there is an example of how the URL of an Instagram video can be retrieved using the newly added functionality.
The first Analysis tab allows you to query the InVID context aggregation and analysis service developed by CERTH-ITI. In a nutshell, this service is an enhanced metadata viewer for YouTube, Facebook and Twitter videos that allows you to retrieve contextual information, location (if detected), most interesting comments, apply reverse image search and check for tweets on the video (on YouTube). Be aware that the service may take some time if the video processed has a lot of comments. A new feature (a reprocess button) allows you to refresh the analysis.
The second Keyframe tab is an iframe opening the website of CERTH-ITI on video fragmentation. It allows you to copy a video URL (from Youtube, Twitter, Facebook, DailyMotion or Dropbox) or upload a video file (in mp4, webm, avi, mov, wmv, ogv, mpg, flv, and mkv format) in order to segment it in keyframes which then can be searched with a right click on Google, Yandex, Tineye and Baidu images. Our service extracts a rich set of keyframes (depending on the variation of the visual content of the video) and therefore gives the opportunity to enhance the video reverse image search. Those are the real video keyframes that differ from the thumbnails served by Youtube or Facebook. Last but not least, to strengthen more the reverse image search process, the service provides more keyframes on demand, after clicking on the “More keyframes” button that is placed at the end of the initially provided collections of keyframes.
The Thumbnails tab allows you to quickly trigger a reverse image search on Google, Bing, Tineye or Yandex Images with the four thumbnails extracted from a Youtube video. Up to four tabs (according to the number of thumbnails available) are opened automatically in your browser with the results of the reverse search while the four thumbnails are also displayed in the plugin page. This tab is somewhat redundant with what can be done with the Analysis tab but it is very fast and efficient if you just need to look whether a Youtube video has already been published previously. Please note that the Chinese search engine Baidu is not implemented here because it is filtering out Youtube content.
The Search tab allows to enhance a Twitter advanced search for keywords or hashtag using the since and until operators, either separately or together to query within a time interval, up to the minute. It translates automatically the calendar date, hour and minutes into an unix timestamp to facilitate the query, e.g. of first eyewitness pictures or videos within a time range just after a breaking news event. We have also added other features from Twitter advanced such geocode, near, from, language and various filter operators.