Using Social Media to Predict Criminal Behaviour 1
Using Social Media to Predict Criminal Behaviour
Mandy Roosendaal, 2663488
Psychology, Big Data in Psychology
Marisa Huisman, group 1
Word count: 1409
31-01-2020
, USING SOCIAL MEDIA TO PREDICT CRIMINAL BEHAVIOUR 2
Using Social Media to Predict Criminal Behaviour
According to Gibbons (1987), criminal behaviour is one of the biggest issues in today’s
society. He defines criminal behaviour as a range of behaviours involved with breaking the law.
He also states that it is such a big problem because it often induces harm to others. Javidi and
Yadollahie (2012) found that up to 75% of crime victims develop post-traumatic stress disorder,
and this number rises to up to 80% for rape victims. Post-traumatic stress disorder is described as
an anxiety disorder triggered by exposure to actual or threatened death, serious injury or sexual
violation by the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5;
American Psychiatric Association, 2013). According to Pieters (2019), crime rates have
increased by 5% in the first quarter of 2019 as compared to the first quarter of 2018 in the
Netherlands. This is the first time in five years that crime rates have increased in the Netherlands.
As criminal behaviour is a very big issue, it is important to stop crime rates from increasing
again.
To prevent something from happening, such as criminal behaviour, it helps to know when
and where it will occur. This way, the necessary precautions can be made. A big data approach is
needed to predict criminal behaviour because it will help to make detailed predictions in a large
area; the Netherlands. Without big data, the predictions would be restricted to one small area and
even then, crucial details would be missed out on. Williams, Burnap, and Sloan (2017) found that
the big data approach has already helped to make more detailed predictions in a large variety of
fields aside from criminology. For example, the frequency of tweets and their sentiment related
to a movie predicted the revenue of the movie better than the Hollywood Stock Market. This
indicates that big data from social media may also help predict criminal behaviour better than the
algorithms currently in use by the Dutch police. According to Saunders, Hunt, and Hollywood
Using Social Media to Predict Criminal Behaviour
Mandy Roosendaal, 2663488
Psychology, Big Data in Psychology
Marisa Huisman, group 1
Word count: 1409
31-01-2020
, USING SOCIAL MEDIA TO PREDICT CRIMINAL BEHAVIOUR 2
Using Social Media to Predict Criminal Behaviour
According to Gibbons (1987), criminal behaviour is one of the biggest issues in today’s
society. He defines criminal behaviour as a range of behaviours involved with breaking the law.
He also states that it is such a big problem because it often induces harm to others. Javidi and
Yadollahie (2012) found that up to 75% of crime victims develop post-traumatic stress disorder,
and this number rises to up to 80% for rape victims. Post-traumatic stress disorder is described as
an anxiety disorder triggered by exposure to actual or threatened death, serious injury or sexual
violation by the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5;
American Psychiatric Association, 2013). According to Pieters (2019), crime rates have
increased by 5% in the first quarter of 2019 as compared to the first quarter of 2018 in the
Netherlands. This is the first time in five years that crime rates have increased in the Netherlands.
As criminal behaviour is a very big issue, it is important to stop crime rates from increasing
again.
To prevent something from happening, such as criminal behaviour, it helps to know when
and where it will occur. This way, the necessary precautions can be made. A big data approach is
needed to predict criminal behaviour because it will help to make detailed predictions in a large
area; the Netherlands. Without big data, the predictions would be restricted to one small area and
even then, crucial details would be missed out on. Williams, Burnap, and Sloan (2017) found that
the big data approach has already helped to make more detailed predictions in a large variety of
fields aside from criminology. For example, the frequency of tweets and their sentiment related
to a movie predicted the revenue of the movie better than the Hollywood Stock Market. This
indicates that big data from social media may also help predict criminal behaviour better than the
algorithms currently in use by the Dutch police. According to Saunders, Hunt, and Hollywood
