This HTML5 document contains 64 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

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Statements

Subject Item
dbr:Documenting_Hate
rdfs:label
Documenting Hate
rdfs:comment
Documenting Hate is a project of ProPublica, in collaboration with a number of journalistic, academic, and computing organizations, for systematic tracking of hate crimes and bias incidents. It uses an online form to facilitate reporting of incidents by the general public. Since August 2017, it has also used machine learning and natural language processing techniques to monitor and collect news stories about hate crimes and bias incidents. As of October 2017, over 100 news organizations had joined the project.
dbp:name
Documenting Hate
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dcterms:subject
dbc:Hate_crime dbc:Natural_language_processing dbc:Knowledge_bases dbc:Data_mining dbc:Data_journalism dbc:Social_statistics dbc:Applications_of_artificial_intelligence dbc:Media_analysis_organizations_and_websites
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1093231275
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dbc:Hate_crime dbr:Bias_incident dbr:The_Boston_Globe dbr:Vox_(website) dbc:Natural_language_processing dbc:Knowledge_bases dbr:Georgetown_University dbr:Information_Technology_and_Innovation_Foundation dbr:Data_visualization dbr:Hate_crime n12:Logo_for_the_Documenting_Hate_project.jpg dbr:Data_science dbr:The_Hoya dbr:Google dbr:Natural_language_processing dbr:2016_United_States_presidential_election dbc:Data_journalism dbc:Data_mining dbc:Social_statistics dbr:Machine_learning dbr:Unite_the_Right_rally dbc:Applications_of_artificial_intelligence dbr:Journalism dbr:ProPublica dbr:The_New_York_Times dbc:Media_analysis_organizations_and_websites
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dbp:country
United States of America
dbp:established
2017-01-17
dbp:founder
dbr:ProPublica
dbp:logo
n12:Logo_for_the_Documenting_Hate_project.jpg
dbp:products
News and data on hate crimes and bias incidents
dbp:type
dbr:Data_science dbr:Journalism
dbo:abstract
Documenting Hate is a project of ProPublica, in collaboration with a number of journalistic, academic, and computing organizations, for systematic tracking of hate crimes and bias incidents. It uses an online form to facilitate reporting of incidents by the general public. Since August 2017, it has also used machine learning and natural language processing techniques to monitor and collect news stories about hate crimes and bias incidents. As of October 2017, over 100 news organizations had joined the project.
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