# Computational Social Science of Disasters: Opportunities and Challenges
## 3 Computational Social Science
### Online Crowdsourcing and Field Experiments  
Internet technologies have opened new frontiers in social collective action and knowledge and the gathering of scientific data in the forms of online crowdsourcing and digital field experiments (see [153; 154; 155; 156; 157] for reviews). Crowdsourcing can be understood as the leveraging of information technologies for individual participation in collective processes [158], such as crowdfunding, mapping applications such as Waze, and citizen science data collection efforts (e.g., Christmas Bird Count [159] and Geo-Wiki [160]). Internet platforms such as Waze, Airbnb, and Ushahidi's [161] crisis mapping applications aggregate individual action and knowledge with computational tools that enable individuals to address ongoing social problems. A significant new set of tools in the hands of computational social scientists are micro-tasking sites, such as Amazon Mechanical Turk, that provide a virtual environment for social science experiments.  
Experimentation is the primary means for establishing causal relationships, and the cyber world is providing new opportunities and challenges for researchers to conduct large-scale experiments [156]. On the one hand, the \"field\" of the experiments, i.e., the Internet, narrows down the scope of the interventions only to those applicable in the cyber world, and it limits the ways subjects can be tracked. On the other hand, the increasing variety and prevalence of web applications in daily social life allow experiments with larger and more diverse subject pools in a shorter period of time and with greater participation. Researchers from different fields have conducted both field- and lab-like experiments in cyberspace to test the effects of controlled or natural interventions using various social computing platforms (for a recent survey of online field experiments, see [157], and for lab-like experiments, see [162]). In disaster studies, they have been used to look at crisis communication and emotions in [PERSON] et al. [163], public behavioral responses to disaster information provided online in [PERSON] et al. [164], and purchasing behavior post-Fukushima nuclear accident by [PERSON] and [PERSON] [165]. [PERSON] [166] provides examples of how experimental approaches in studying social computing systems can improve the design of such systems and advance our understanding of human behavior in crowd-tasking activities during crisis mapping. The online platforms available for \"field\" experiments include micro-tasking sites (e.g., Amazon Mechanical Turk [167]), question and answer sites (e.g., Stack Overflow [168]), collaborative encyclopedias (e.g., Wikipedia [169]), social networking sites (e.g., Facebook [170]), e-commerce sites (e.g., eBay [171]), massive open online courses (e.g., Coursera [172]), sharing economy sites (e.g., AirBnB [173]), dating sites (e.g., OkCupid [174]), massively multiplayer online games (e.g., World of Warcraft [175]), or other platforms over which experimenters can exert greater control (e.g., their own sites [176]). Technologies used for interventions in these experiments include emails with different contents [177], websites with different looks [178], bots with different strategies (server-side scripts) [169], and browser extensions with different pop-up behaviors (client-side scripts) [179].  
In this section, we briefly review the computational methods developed and used to support social science inquiries with new techniques in computational models and data analysis. We also discuss how CSS provides open-source data, new theories of decision-making, social processes of aggregated behavior, complex adaptive systems, and spatial and network structure, and new experimental methods in online field experiments and social simulations. We now shift our focus to an area where computational methods intersect with disaster research and practice but do not necessarily address traditional social science research questions.