Exploring Data on Crimes in Singapore
Recently, a friend and I were assigned to do a small group project together. For this project, our professor gave us a topic and we were told to find data and come up with a deliverable that could be posted online. This article will follow our process as we attempt to make graphs that could be posted on Reddit.
The topic given to us was “Criminal Justice”. It was broad and neither of us was experts on this subject. So the first thing we did was turn to Google. We browsed through the web and Googled related keywords in hopes that something would inspire us. Luckily for us, we came across this dataset containing the number of victims of selected major crimes in Singapore. We still didn’t know what to do with the data, as the dataset was already pretty clean and neat. So we played around with it and decided to make a quick graph just to see the trends of different kinds of crimes in Singapore and we ended up with this:
We quickly realised that the graph was not going to be very useful for gaining quick insights given how flat most of the trendlines were, making it hard to analyse any changes in the trends. The issue was that the scale for “Cheating and Related” crimes was much larger than the other types of graphs, which led to the flattening of the other trendlines. To overcome this, we decided to create a secondary axis so that we can better observe the changes in the trends of all major types of crimes.
We posted this graph onto Reddit and received some feedback. Someone commented that the use of the secondary axis was confusing and we did agree with him but we felt like in order to produce meaningful insights, it was either this or create two separate graphs. There really was no good way out of this and we decided to go with the secondary axis. Another Redditor also suggested that we just drop the “Cheating and Related” crimes trendline but we did not want to since we felt that was one of the more interesting trends that we could analyse.
Moreover, this process highlighted to us how the categories that the government has used to group the various crimes can be really confusing and concerning. This sentiment was also shared by some Reddit users who had seen our graph posted on Reddit, as seen from the image below.
This brings out an important sociological concept that is worth discussing which is beyond the scope of this article. How the Singapore government portrays information to the public. We say portray here because the information is carefully presented to the public. For instance, the range of cases under the broad category of “outrage of modesty” or “cheating” can be really wide in terms of the severity of each crime under each category. Some food for thought will also be: Could Singapore’s government be trying really hard to mask these issues to ‘protect’ its citizens from harsh truths?
Some of the comments did provide some constructive feedback and we took their suggestions and edited our original graph to repost on Reddit.
We thought it was interesting to see the different trends of different kinds of crimes in Singapore. Having lived here for so long, both of us tend to see Singapore as a generally safe place with low crime rates. While overall crime rates are still low, this graph tells us that the rate of certain kinds of crimes, namely cheating and outrage of modesty, are increasing.
To explain the increase in these crimes, we have come up with these possible explanations, or “hypotheses”, if you will:
- The increase in outrage of modesty crimes is not because more people are committing acts of molestation but rather more victims are stepping up to report such crimes.
- The increase in cheating and related crimes is due to high usage of technology in Singapore combined with low levels of media literacy, especially amongst the elderly.
To see if our hypotheses were true, we went to do some of our own research and here is what we found:
Hypothesis 1: We feel that the increase in outrage of modesty crimes, is due to the possibility of more people stepping up and reporting these crimes especially because of social movements like the #metoo movement or even the Monica Baey incident. Effectively, more people are less afraid of coming out to report those particular crimes.
To support our hypothesis, we started further researching this idea and on social movements related to sexual violence and crimes in Singapore, and we came across various interesting articles.
According to this article published on Forbes in December 2017, there might be an induced Weinstein Effect which is basically about how the revelation of producer Harvey Weinstein’s predatory behaviour by famous actresses led to newer and many other women’s revelations about sexual misconduct by men in powerful places. This effect eventually sparked the #MeToo movement on social media which has rallied many victims’ voices and the article hints at a similar situation in Singapore as well.
“Since the start of the #MeToo movement, SACC’s calls have doubled from 35 to 70 cases per month. According to Lim, “#MeToo has emboldened victims in Singapore to seek help from SACC and to find out what their rights and options are. There has been less public calling out, unlike in the West, probably because of cultural reasons.”
Inspired by the #MeToo movement, a sexual assault survivor in Singapore has recently started Hear to Change, an online platform to support people who have experienced sexual harassment. The website allows survivors to share their experiences of sexual abuse anonymously, and so far, they have received on average one story per day.” (SACC stands for Sexual Assault Care Centre)
The #MeToo movement was originally started by Ms Tarana Burke in 2006, and it started in 2006, to promote “empowerment through empathy” for females of colour who were sexually abused. The movement saw different phases. According to our graph above, one can see the significant increase in the cases reported for outrage of modesty from 2016 onwards. And so we asked why. And this is what we found:
In 2016, there was another case of sexual assault that was spoken about on social media that went viral. It was a post by Ukranian journalist Anastasia Melnichenko. However, she used the hashtag: #IAmNotAfraidToSpeak.
Although we feel that this may not have affected Singapore that much, this could be a possible reason that can explain the increase in the number of cases being reported from 2016: social media has become a platform for people to step up and open up, and fewer people are afraid, hence more people are reporting.
A more plausible explanation could be the start of the Outrage of Modesty campaign by the Singapore Police Force (SPF). While we couldn’t find an exact date the campaign started, we can kind of guess that it has been around since at least 2015 based on this article in Youth.sg where the writer talked about victim-blaming in Singapore. This campaign basically involved putting up posters in public spaces, such as in buses or trains, telling victims to speak up in the event they were molested. This could have helped victims speak out as they would be more certain of how to report such crimes.
We’re not sure what exactly caused Singaporeans to be more outspoken against such issues, whether it really was the influence of these movements but we know that social media has played a role as a platform for victims to step up. This can be seen from how Monica Baey used Instagram to garner support regarding the assault on her that went viral in Singapore. Read this for a summary of the timeline of events that transpired: https://alvinology.com/2019/04/23/monica-baey-nus-nicholas-lim-instagram-petition/.
To take this a step further, we wanted to understand if this is specific to Singapore or if it is a worldwide phenomenon. Hence, we tried searching for similar datasets from different countries, which we were successful in finding. However, it was not apt for us to compare Singapore’s data with other countries because of the different categories that the different datasets used. For example, in Singapore’s dataset, we had two separate categories for Rape and Outrage of Modesty. Whereas other datasets, for instance, the US, have rape, but not outrage of modesty, or we are unsure if it is accounted for under one category. Hence making a deduction based on a comparison across the datasets from different countries would have rendered invalid (the validity of a dataset or a claim based on a dataset effectively shows the extent to which the results really measure what they are supposed to measure).
Hypothesis 2: We felt that the increase in cheating and related graphs made sense given how much technology Singaporeans use on a daily basis. According to a study done by Hootsuite in 2017, about 84% of Singaporeans are internet users with 93% of these users surfing the Internet daily. Out of these numbers, a significant amount consists of the elderly, who are most vulnerable to online scams. This article from Today explains in depth why this is the case but to summarise: The elderly are most vulnerable to cyber scams because they are most likely to be targeted and most likely to fall for scams.
Our dataset also included the age groups of the victims who fell for cheating and related crimes so we wanted to play around with it to see if the elderly were scammed more than younger people. We came across an issue though and that was we quickly realised that the age groups were not categorised as nicely as we wanted it to be. Rather than the usual “10 to 19”, “20 to 29”, etc. kind of age groups that we wanted, the dataset only gave us two groups: “below 21” and “21 and above”.
Sure it did show us that more people aged above 21 were victims of cheating crimes but it was not as insightful or useful as we had hoped. Firstly, the number of people aged 21 and up is a lot more than the number of people aged below 21. Secondly, this doesn’t tell us if the elderly, those aged 65 and up, were getting scammed more than other categories of adults. The data was in a way ineffective in categorisation.
To conclude, we understood that any dataset can be insightful if we do further analyses and research on it, it is important to look at the datasets, know it and start asking “why” which will eventually lead us to find out more. In this way, data is hypothesis-generating, it doesn’t necessarily directly answer questions, rather it gives us an idea of what questions to ask and what answers to seek.
It is also interesting to note on the side that not all sorts of data are made available by the Singapore government. Initially, when were finding data on executions, data for specific years were not released at all. This brings up another question of data protection in Singapore and why it matters to this country. Do share with us your opinions on closed vs open data. What should be made available and what should not be?
