When we examined algorithmic data analysis and network analysis, the main aim was to analyse data with a computer. With simulation models, we showed benefits beyond analysing data sets and instead benefited from computers' capabilities to calculate and thus generate working simulation models. However, the capability to execute huge numbers of calculations is not the only area that can benefit from how they are used. Computers are used in interactive systems, where a user interface interacts with the computer. A computer system responds to usersâ commands in (almost) real-time fashion. When you are driving a car in a car game and turn your wheel left, the computer interprets this as a command and responds by changing the direction of the car and adapting the scenery displayed to you to correspond to the new direction. Compared with this type of close interaction and feedback loop, algorithmic data analysis, network analysis and simulation models were rather static in this interaction paradigm. Commands are written in and used to explain what should be done, and the emerging results are then investigated. This interactivity facilitates several opportunities to use computers beyond static analysis. We can create digital systems to study how people interact in specific situations. We call this constructive research as the knowledge is produced through development and construction of digital systems and examines how it is used (Oulasvirta and Hornbæk, 2016). This research approach has been acknowledged in human-computer interaction, design research and engineering. However, there are several reasons to utilise constructive research approaches for social sciences as well.
First, constructed interactive systems can be used to carry on larger-scale experiments and study how people behave in digital environments. For example, Salganik et al. (2006) studied social norms in a 14,341-participant experiment. Similarly, Bond et al. (2012) studied the impact of social influence on voting in a 61-million-participant experiment, and Kramer et al. (2014) explored emotional contagion in social media services with over a half-million participants. While the research approach is similar to traditional social science studies, the number of participants is clearly beyond the scope of non-digital (and non-computational) studies. Furthermore, modern immersive environments can provide more control to experimental conditions than what is usually seen possible. This allows further engagement with novel kinds of research approaches, thus inviting us to use sociological imagination.
Second, interactive systems create new ways of understanding social science theories through seeking to materialise them. Interactive systems are crafted through extensive design work, which can be research-oriented. Research through design is a methodological framework to produce valuable academic insights (Ylirisku et al., 2015; Zimmerman et al., 2007). The essence is that design work is used to reflect how and why particular choices were made, what reactions emerge from potential users and what this all tells us about humans and their behaviour. This work has just recently been gaining ground in traditional social science disciplines. For example, Lupton (2018) highlights these opportunities under an umbrella term: design sociology. She highlights how these design approaches `offer many opportunities for sociologists to expand their research horizons, particularly in relation to applied, practiceâbased, socio-material and futureâoriented research'. Nelimarkka et al. (2019) use prototypes to understand how people perceive polarisation will play out. Therefore, a constructive research paradigm also creates new ways of gaining knowledge.
Looking at the landscape, we highlight how interactive systems may change the landscape for experimental social sciences. The impacts include scale (and speed and cost) of experiments but also open novel opportunities of how to conduct experimental studies. Thus, interactive systems can be seen as research instruments that are constructed using programming. Later in this chapter, we discuss other opportunities to use constructive approaches for social science research. In this case, we do not require programming as such but invite adapting methods and practices from computer sciences. In this approach, the interactive system is a research outcome - not an instrument used to conduct further inquiries.