Investigating Sherlock Holmes: Using Geographic Profiling to Analyze the Novels of Arthur Conan Doyle

• Published in: The Professional geographer Vol. 72; no. 4; pp. 566 - 574
• Main Authors: Stevens, Michael C. A., Ray, Gillian, Faulkner, Sally C., Le Comber, Steven C.
• Format: Journal Article
• Language: English
• Published: Washington Routledge 01.10.2020; Taylor & Francis Ltd
• Subjects: análisis de patrones de puntos; Bayesian statistics; Crime; criminology; criminología; datos espaciales; estadística bayesiana; Family physicians; Geography; Information processing; mapeo de literatura; mapping literature; point pattern analysis; Profiles; Spatial analysis; spatial data; 点模式分析; 犯罪学; 空间数据; 贝叶斯统计
• ISSN: 0033-0124; 1467-9272
• DOI: 10.1080/00330124.2020.1758575

Central to spatial analysis of crime is the assumption that the offender has visited the locations analyzed. We show that even if this is incorrect, meaningful patterns can be identified. Using 390 locations from the Sherlock Holmes stories, we show that geographic profiling (GP) ranks Conan Doyle in the top 13 percent of 2,678 historical figures in London, despite the fact at the time of writing he had not visited all of the sites. Restricting the analysis to thirty authors contemporary with the Sherlock Holmes stories, Conan Doyle ranks first, with a hit score of 2.8 percent (above Holmes's address at 221b Baker Street). Finally, we show that GP prioritizes sites strongly associated with Conan Doyle (example.g., his home) compared to those more tangentially associated with him, even when sites are close together. Our analysis, although mostly for amusement, underlines the ability of GP to extract useful information from complex data.