Welcome to the "1981 and 2011 Riots Redefined: Digitally Deconstructing "Criminal" Narratives" project, which focuses on analyzing and re-narrating dominant histories of the 1981 and 2011 riots in the U.K. more critically and transparently with the help of digital tools.
I created this project to guide data journalists and digital historians in most effectively utilizing humanities-driven data construction and transformation, visualization, mapping, and textual analysis practices. In the upcoming sections, I present how one can identify the problem of dominance of the U.K. Government's "criminal" narrative in data constructions and visualizations on the riots of 1981 and 2011, reinforcing the marginalization of data on rioters' motivations. I then propose several multi-level solutions to the problem, explaining the approaches for transforming the data sources, building interactive visualizations and maps, and extending them with the critical discourse analysis of textual data on riots.
I begin with the section “The Issue of Representing Riots”, by first identifying the problem behind this project and discussing how we can represent and misrepresent the histories of riots and how digital humanities research can help more critically identify and mitigate such a problem. I further support the problem identification by conducting a historical analysis of how the British government viewed the 1981 and 2011 riots and synthesizing key arguments of existing scholarship on the histories of riots in the United Kingdom. I apply this theoretical problem analysis to analyzing dataset constructions of 1981 and 2011 and identifying how the problem is reflected in these data sources.
Following the identification of the problem, I start proposing a multi-level solution to such a problem in sections “Analyzing and Transforming the Data Sources,” “Visualizing the Data Sources,” “Mapping the Data Sources,” “Employing Language Analysis to the Data Source,” which include the following technical approaches:
- Transforming the Data Sources with Python
- Visualizing the Data Sources with Google Data Studio
- Mapping and Remapping the Data Sources with ArcGIS and Google Data Studio
- Employing Language Analysis with Google's NL API and Apps Script
For such project approaches, I identify and transform the following publicly available data sources on the riots of 1981 and 2011:
| Creator(s) | Original Data Source Link(s) | Transformed Data Source Link(s) |
| The Guardian (2011) | “UK RIOT LOCATIONS” | “2011 Riot Locations Dataset” |
| The Home Office (1982, 2011) | (1) "A geographical perspective on the 1981 urban riots in England" (2) "An overview of recorded crimes and arrests resulting from disorder events in August 2011" | “1981 and 2011 Riot Arrests Dataset” |
| Newburn et al. (2015) | "‘The biggest gang’? Police and people in the 2011 England riots" | “Capstone Interviews 2011 Dataset” |
Starting with transforming the data sources - I consider The Guardian’s data set as an example and outline how we can utilize Python to transform the data and address assessing different historical arguments pertaining to our research. I will explain how we can most effectively and interactively visualize our data sources in Google Data Studio. I will then explain how we can geospatially represent different data sources using ArcGIS and Google Data Studio, including the data with interview responses of 2011 riot participants and noting the benefits and limitations in relation to mapping and re-mapping our data sources. Finally, I will outline the significance of using and steps to computationally implement Critical Discourse Analysis, using Google’s Natural Language API and Entity Sentiment Analysis (ESA), analyzing and interactively visualizing sentiment of The Guardian’s and riot participants’ interview response data sources. In the final step, I utilize two ESA-transformed data sources, linked below:
| Original Data Source Link(s) | Transformed Data Source Link(s) | ESA-Transformed Data Source Link(s) |
| “UK RIOT LOCATIONS” | “2011 Riot Locations Dataset” | “Authority and Event Description Data Sentiment Analysis” |
| "‘The biggest gang’? Police and people in the 2011 England riots" | “Capstone Interviews 2011 Dataset” | “Interview Response Data Sentiment Analysis” |
Thus, throughout this guide, I present a solution to a project’s problem - a practical framework leveraging data documentation systems, interactive visualizations, and text analysis tools, emphasizing ethical and evidence-based practices for journalism projects utilizing data on riots and their participants. I invite you to follow along, first to take a more theoretical and historical overview of the topic, which will lead us to a more contextualized use of digital tools (Python, Google’s Data Studio, NL API, Apps Script) to solve the problem behind this project in a more complex and critical way.