Starting out in Computational Social Science

Skills needed to start a CSS career and industries that hire CSS professionals

This post was written for and originally appeared on SAGE Ocean

It’s an exciting time to be in social science. Social media, digital identities and the world of big data has opened up new ways for social scientists to study and examine social phenomenon.

Some examples include using online search patterns to predict the spread of disease, tracking near real-time Twitter data to understand political movements or using location data to understand interpersonal interactions.

The move to a digital world has created an innovative new area of social science called computational social science (CSS).

CSS brings together social science specialisms like economics, political science or sociology and combines this social science expertise with skills in data science, computer science or analytics.

Researchers use their social science knowledge alongside programming and statistical software coding skills to extract data, analyze trends and look for insights on social science issues.

This article offers some of my thoughts on how to move into the CSS field and employers who routinely recruit computational social scientists.

Skills

Let’s start with the skills needed to move into the CSS field.

Social science training — This is the first and most obvious place to start. Social science has a myriad of fascinating sub-groups like economics, sociology and anthropology. Find the right degree and social science specialism, learn as much as you can. Make sure you choose a course with substantial statistics components so that you know how-to analyze the data later on.

Technical skills — This is the set of skills that will help you extract and analyze data. I’ve bucketed the technical skills into three areas:

1. SQL — SQL is the language of databases and a must-know. It has been around for decades and is a staple of the analytics space. SQL is how you will query, sort, and make sense of data in a database. Go to W3Schools, they have a great set of online, interactive SQL classes. If you finish the W3Schools SQL classes, you’ll be in great shape.
2. Statistics Coding — Once you can access the databases and extract data with SQL, you’ll need to know how to analyze it. This is where you’ll use statistics software and coding. Popular packages include: R, Python, SAS, SPSS and MATLAB. R or Python would be my recommendations due to their strong community support and open-source licensing but there are other options. I highly recommend some basic courses to start and then quickly moving into practice-based learning. I spent a chunk of time learning-by-doing and found it the best way to understand the code.
3. Visualization — Visualization is an important skill to communicate your learning and insights. I regularly see great analysis relegated to a dusty shelf because of poor communication and visualization. For this reason, I recommend learning some basic design skills, basic data visualization best practices and visualization packages. Tools include: Plotly, Google Charts, FusionCharts, HighCharts, DataWrapper, Tableau and Qlik. You can also create data visualization through packages in R and Python.

In summary, you’ll be looking to combine your social science education with SQL, statistics coding and visualization skill sets. This will provide a solid foundation for starting a career in CSS. You don’t need to be an expert in all of these areas when starting out as there is a lot of on-the-job learning with CSS but, good coverage of these four skill sets will provide the tools you need to get started in CSS.

Industries that Hire CSS Professionals

Now that you have the skills, you’ll probably want to look for a job. In this section I’ve listed out the industries that typically hire CSS professionals. It is based on my personal experience so it is not exhaustive but should provide a good start to your CSS job hunt.

Academia — Academia is probably one of the largest employers of social scientists. CSS professionals can work on a diverse array of research areas while teaching and publishing.

Technology Industry — Google, Facebook, Intel and Salesforce all hire large numbers of CSS professionals in fields like user experience research, data science, decision science, marketing sciences and product research. I currently work in this area.

Government — Government bodies are also large employers of social scientists. Economists might work in Treasury departments, researchers might work in Social Services and data scientists in areas like Health or Education. I’ve personally worked in both national (federal) government and state government institutions.

Non-profit and Community Organizations — Non-profits and community-based organizations are fast discovering the power of big data and also realizing that data is becoming more accessible. I have several friends who are CSS professionals working with charities to help them digest and use data to improve their service delivery.

Management Consultancies — Management consultancies are also realizing the power of big data and hiring a swath of data-savvy professionals that can help them and their clients use data insights more effectively. Consultancies are often looking for user researchers, data scientists, business intelligence professionals and decision scientists.

Banks and Insurance Companies — Banks and insurance companies have massive treasure troves of user data and while the financial industry has long hired statisticians, they are also seeing the value of social scientists who bring a unique, human-centered lens to data analysis and can understand social patterns hidden in the data.

A Few Last Recommendations

A few last thoughts as you think about a career in CSS.

Try lots of things. Whenever I hire or work with a more junior analyst, I recommend they try a broad range of projects early in their careers. Trying different projects will help you find the skills and topics you find most interesting. In my opinion, this is one of the most important journeys you will take and so it’s worth the time investment early on. You could volunteer for projects, take a secondment, work in a different country or try different job hats. Take the time to evaluate each experience based on what you liked and didn’t like. This will help you understand areas of work that give you energy and the areas that are less exciting.

Focus is your friend. As you get to learn what you enjoy and don’t enjoy, I suggest developing one or two specialisms. That way you’ll have your broad skills in CSS alongside one or two specialisms that will set you apart as a CSS professional. Also, studies show that specialists are often paid more and are more in-demand which is always nice.

Last but not least, communication is key. Data scientists and analysts don’t have the best reputation when it comes to communication. So it should come as no surprise that analysts or researchers who do communicate well tend to have an edge when it comes to promotions and job opportunities. You don’t need to be the best public speaker but being able to explain and visualize your insights in a digestible way is a huge asset that will serve you well throughout your career.

As I mentioned, it’s an exciting time in social science with big data opening up a world of new opportunities to study and evaluate social trends.

Opportunities to use vast databases of information to study social science at scale are now available to CSS professionals that have never existed before. I expect those opportunities will keep growing as data analysis tools develop and as governments open up more and more data sets to researchers and scientists.

So, if you are passionate about the social sciences and are interested in data analysis at scale, computational social science could be the place for you.

This post was written for and originally appeared on SAGE Ocean. SAGE Ocean is an initiative from SAGE Publishing to help social scientists navigate vast data sets and work with new technologies. Our hope is that our work will help to make it easier for social researchers to work with big data and new technology in order to advance our understanding of the world.