Extraction and geo-referencing suburban locations of terroristic attacks from textual data of Maiduguri insurgency

Abstract

There are no precise suburban coordinates of location of terrorism attacks in parts of Maiduguri. Effort to apply geospatial analysis will require such data. The objective of this study was to enforce georefencing to textual global terrorism databases, particularly for Maiduguri, such that it will provide basis for geospatial analysis and planning counter terrorism. Global terrorism data were sourced from Internet and reduced to Maiduguri and its surroundings. The textual aspect of the databases that reported attacks were used to extract the phrases containing prepositions that indicated location of the attacks at suburban level (such as wards). The phrases were cleaned in order to bring out the names of the locations of attacks. A reference location data (RLD) was developed from OpenStreetMap (OSM) and the Nigerian Administrative boundary (SURCON, 2022) and used in determining the coordinates of the locations using Microsoft Excel Fuzzy look up. Half of the extracted names could not be determined from the OSM based RLD. The names that could not be found were looked up and determined from the Google Earth. The preposition ‘in’ and ‘at’ were the most useful, returning most of the extracted location. Other indicators of locations such as: ward, area and neighbourhood merely repeated what the two prepositions have determined. The process extracted 188, 273 and 169 geospatially records for Global Terrorism Database (GTD), Gedevents and Armed Conflict Location and Event Data Project (ACLED) respectively. This work demonstrated that global data on terroristic attack can be used to determine suburban location of attacks. Conversely, tracking terroristic attacks should include suburban locations. The key to determining the coordinates of a suburban location is a robust reference dataset, which can be updated. This work provided the basis for geospatial analysis and hence counterterrorism efforts.