Approaches to mapping hate speech online can be classified into three principal groups based on their purpose:
- Real-time monitoring and mapping: These projects, the best known of which is the Umati project in Kenya, aim to provide continuous monitoring of online media. Such projects are rare, but they have the potential to serve as early warning systems or enable a reaction to incidents as they occur.
- Retrospective monitoring and mapping: It has been more common to carry out analysis of online hate speech after it has happened by looking at archives of messages or collecting messages for a short time and then analysing them.
- Discourse and content analysis: These approaches examine potential hate messages within their social and political context to understand the meanings, motivations, and ideologies behind the messages, and to unpick the components of a message and its delivery. They do not aim to track trends in frequency or location, but to understand how hate messages are constructed and how they influence recipients.
Until recently, approaches to monitoring hate speech have relied on human analysts reading and classifying suspected messages, but attempts to apply automated techniques drawn from the field of corpus linguistics are increasing. They have potential to process the massive amounts of data that can be collected through monitoring social media, and to operate in real time. However, they have so far had only limited success in dealing with the highly context-dependent nature of online hate speech.
Very few hate speech monitoring projects have been linked with programmatic activities to combat hate speech. During the 2013 Kenyan elections, the Umati project was linked with the Uchaguzi project which had a broader election monitoring mission and which referred instances of hate speech onwards to appropriate authorities. Most projects that we identified for this report only aimed to publicise and expose hate speech, or undertook after-the-fact analyses, and were not designed to respond to incidents.
