Category: Uncategorized
Comparing Human And Machine Transcripts: A List Of Common Differences
How do the automated television news transcripts generated by Google's Cloud Video API compare with the human-produced captioning viewers see?…
Using Automated Speech Recognition To Precision Align Human Closed Captioning
Human-generated closed captioning remains the gold standard for live television news broadcasts, but the use of human transcriptionists to listen…
Trump's Tweets Aren't Getting The Same Television News Attention They Did In 2017
President Trump has eschewed many of the traditional presidential communications norms to speak directly to the world through his @realDonaldTrump…
Visual Global Entity Graph 2.0: Master Visual Entity List
Google's Cloud Video API recognizes an incredible range of objects and activities, allowing the Visual Global Entity Graph 2.0 to…
Television News Global Entity Graph 2.0: Now Live Updating
The Television News Global Entity Graph 2.0 announced yesterday is now live updating every 30 minutes, with most shows being…
What Google's Natural Language API Sees In A Decade Of Television News: The Television News Global Entity Graph 2.0
What might it be like to use deep learning algorithms to non-consumptively "read" the closed captioning transcripts of more than…
New York Times: Which Democrats Are Leading the 2020 Presidential Race?
The New York Times' look at the 2020 Democratic field uses the TV Explorer to examine media coverage of the…
Visual Narratives: A Fracturing of the Nightly News
When we tune into television news, how different are the stories and perspectives we see on each channel? This fundamental…
Visual Global Entity Graph 2.0: Visual Similarity At The Semantic Level
Historically, evaluating how "visually similar" two videos are has done through measuring the overlap of their color (and occasionally texture)…
Visual Global Entity Graph 2.0: Assessing The Semantic Visual Similarity Of A Decade Of Television Evening News
To what degree does the view we see of the world around us vary based on the media outlets we…
Visual Global Entity Graph 2.0: Using Semantic Visual Correlation To Identify Mislabeled Television Shows
The new Visual Global Entity Graph 2.0 covers more than 19 million seconds of airtime across four stations spanning ten…
Visual Global Entity Graph 2.0: Tracking Protests On The Evening News 2009-2020
Last year we used the pilot version of the Visual Global Entity Graph to track depictions of protests on the evening…
Visual Global Entity Graph 2.0: Tracking The Increasing Presence Of Police On The Evening News
Last year we used the pilot version of the Visual Global Entity Graph to track depictions of police on the…
Visual Global Entity Graph 2.0: Now Live Updating
The Visual Global Entity Graph 2.0 is now updating every 30 minutes with a rolling delay of 24 hours! Some…
Shining Light On Acronym's Shadow
In the aftermath of the Iowa caucus troubles, many of the organizations that had previously touted their associations with the…
Visual Global Entity Graph 2.0: Now Available In BigQuery
The Visual Global Entity Graph 2.0 dataset is now available in BigQuery, allowing complex at-scale queries in seconds! gdelt-bq.gdeltv2.vgegv2_iatv
Video AI: Comparing Frame Versus Airtime Analytic Resolutions For Content Analysis
Machines watching television news record what they see with frame-level precision, using nanosecond timestamps. Humans performing content analysis on video…
Visual Global Entity Graph 2.0: Raw Full-Resolution API Output Now Available
Using AI to watch a decade of television evening news broadcasts poses fascinating and novel challenges when it comes to…
Decentralized Socio-Technical Services And Applications For The Internet of Things – A Testbed Self-Integration
A fascinating IoT testbed architecture using GDELT's data feeds, by researchers at ETH Zurich and the University of Leeds. Read…
BBVA: Coronavirus Sentiment & Geo-World: Conflict & Protest January 2020
BBVA's latest global risk report includes a unique map of global media reaction to the coronavirus threat: The coronavirus hits…
New York Times: Which Democrats Are Leading the 2020 Presidential Race?
The New York Times' look at the 2020 Democratic field uses the TV Explorer to examine media coverage of the…
Greater Good Gathering 3.0 At Columbia University
Kalev spoke today at the Good Gathering 3.0 held at Columbia University alongside a list of speakers including Robin Chase,…
WSJ: How AI Spotted And Tracked The Coronavirus Outbreak
The Wall Street Journal covers how BlueDot Global's machine learning algorithms sifted the earliest mentions of the Coronavirus from GDELT's…
Born Out Of The 2014 Ebola Epidemic GDELT's Mass Translation Infrastructure Helped BlueDot Identify 2019's Coronavirus
On March 13, 2014, GDELT's global monitoring infrastructure detected the first local media reports of what would go on to…