Researchers in Finland have trained a machine-learning algorithm to identify hate speech by comparing computationally what differentiates text that includes hate speech from text that does not contain hate speech and developing a categorization system for hate speech.
The researchers employed the algorithm on a daily basis to screen all openly available content that municipal election candidates had generated on Facebook and Twitter. The algorithm was taught using thousands of messages, which were cross-analyzed to uphold scientific validity.
"When categorizing messages, the researcher has to take a stance on the language and context, and it is therefore important that several people participate in interpreting the teaching material," says the University of Helsinki's Salla-Maaria Laaksonen.
She says social media services and platforms could identify hate speech if they wanted to, and in that way influence the activities of Internet users.
"There is no other way to extend it to the level of individual citizens," Laaksonen notes.
From Aalto University
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