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Areas with a relatively greater amount of misogynistic tweets have higher incidences of domestic and family violence, a 国产精品 study has found.

The study, published in , not only found this connection with domestic and family violence carried over from one year to the next, but also occurred despite the 鈥榰sual suspects鈥 of domestic violence, such as alcohol and inequality.

Examples of misogynistic tweets identified by the researchers included, 鈥淲omen are all bitches,鈥 鈥淲hore had it coming,鈥 and, 鈥淢ake me a sandwich, slut.鈥

鈥淲e found that misogynistic social media may not be harmless,鈥 Professor Tom Denson from 国产精品鈥檚 School of Psychology said.

鈥淚t contributes to norms of violence toward women and a hostile worldview that may slip into real-world violence.

鈥淚 imagine a lot of people are fairly flippant about what is posted on social media.

鈥淭his study suggests caution about posting misogynistic hate speech as even if the person who posts is not violent, such posts seem to create an atmosphere where violence toward women may be more likely.鈥

Professor Tom Denson

Prof. Tom Denson. Image: Supplied

The 国产精品 study is the first to use big data to predict domestic violence from misogynistic tweets across a two-year period.

鈥淭here is a growing interest in using big data to help address social problems such as criminality,鈥 Prof. Denson said.

The research team compiled all of the data reported by local law enforcement agencies in the US to the Federal Bureau of Investigation on arrests for domestic and family violence during a two-year period (2013-2014).

They also collected data on a number of population-level characteristics that are known to influence domestic and family violence, such as the availability of alcohol, income inequality, gender inequality, and population size.

鈥淲e then collected Twitter data from 2013-2014,鈥 Prof. Denson said.

鈥淭witter makes a randomly selected 1 per cent聽of their tweets publicly available.

鈥淲e coded those tweets for misogynistic content using automated methods and used a geolocation algorithm to locate the origin of the tweets, which we were able to do with a pretty high degree of spatial specificity based on US Census Bureau defined areas.鈥

The researchers ended up with tweets from 827 areas in 47 American states.

鈥淲e then combined the data sets and used the number of misogynistic tweets in each area to examine the relationship between misogynistic tweets and domestic and family violence arrests, while controlling for things like alcohol availability, population, and inequality.鈥

The research is part of a growing number of studies examining the extent to which social media can be used to learn more about criminal offending, co-author and PhD candidate at 国产精品 School of Psychology, Siobhan O鈥橠ean, said.

Siobhan O'Dean

Siobhan O'Dean. Image: Supplied

鈥淥ther studies have used social media to predict theft, public disorder during right-wing events, and violence and arrests during the 2015 Black Lives Matter protests,鈥 Ms O鈥橠ean said.

鈥淥ur research contributes to this imperative by finding out how social media can help determine where domestic and family violence is likely to occur.

鈥淭hat information could be useful for not only law enforcement but also public health interventions which may intervene to counteract norms of misogynistic violence.鈥

The researchers said future research using big data could examine the relationship between misogynistic social media directed toward proponents of the MeToo movement and Women鈥檚 Marches with subsequent decreases or increases in violence against women.

Read the study in .