Legal Responses to Cyber Terrorism in West Africa: A Comparative Analysis of Nigeria’s Cybercrime Act and the ECOWAS Directive
Description
This dataset contains quantitative and qualitative evidence on cyberterrorism governance in Nigeria and the ECOWAS sub-region, focusing on legislative harmonisation, institutional coordination, technical and forensic capacity, cyber intelligence, capacity building, public–private cooperation, and public awareness and digital literacy. The study used a mixed-methods design combining descriptive statistics, Pearson Product-Moment Correlation, standard multiple linear regression, and thematic analysis. The data were gathered through a structured questionnaire and semi-structured interviews. Altogether, 175 participants were recruited via purposive and stratified sampling, with 150 valid responses received, for 85.7% response rate. Respondents included military and paramilitary personnel, academics, relevant Nigerian and ECOWAS agencies, and members of the diplomatic corps. The two hypotheses examined the effects of ECOWAS legislative harmonisation on cross-border cyberterrorism investigations and prosecution, and the contributions of technical, intelligence, capacity, and infrastructure factors to cyberterrorism governance and legislative harmonisation. The findings show moderately high legislative harmonization (mean = 3.20). Most respondents agreed that cyberterrorism definitions and sanctions are harmonized. However, legal divergence and overlapping institutional mandates hinder effective cooperation. Overall, stronger legal alignment and inter-agency coordination are needed to improve regional cyberterrorism responses. Using Pearson correlation, the study found a significant positive relationship between legislative harmonization and cross-border investigation and prosecution (r = .550, n = 150, p = .001). Further, using regression analysis, the only variable that was statistically significant was capacity building (β = .784, p < .05), while technical infrastructure and forensic capability, advanced cyber intelligence, and technical capacity deficiency were not statistically significant. The qualitative analysis produced seven themes; the research results show the need for an integrated and multi-dimensional approach to cyberterrorism governance, including strengthening of legal framework, institutional collaboration, technical capabilities, human capacity, public awareness, partnerships, and enforcement. It is necessary that this dataset be interpreted primarily as stakeholder-perception evidence from a Nigeria-focused study and should not be treated as statistically representative of all ECOWAS Member. The dataset provides Nigeria-focused stakeholder evidence for research on cyberterrorism and regional security cooperation, but users should distinguish between statistical associations, regression results, and qualitative interpretations and avoid interpreting the findings as evidence of causality without further analysis.
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Steps to reproduce
DATA FILES INCLUDED: 1. Quantitative survey dataset – Field Survey, 2026 (N=150). 2. Survey instrument containing four Legislative Alignment items and four Institutional Coordination items. 3. Codebook describing demographic and substantive variables. 4. Statistical output containing descriptive, reliability, correlation, and regression results. SOFTWARE REQUIRED: IBM SPSS Statistics. The software version must match the version used to generate the deposited output. A. DATA PREPARATION 1. Import the respondent-level survey dataset (N=150) into SPSS. 2. Code demographic variables: Gender, Age, Type of Organisation, Years of Experience in Cybersecurity/Counter-Terrorism, and Educational Qualification. 3. Code substantive responses using the four-point scale: Strongly Disagree (SD), Disagree (D), Agree (A), and Strongly Agree (SA). 4. Verify that item coding, variable labels, and missing values correspond to the deposited codebook. B. LEGISLATIVE ALIGNMENT 1. Analyse the four Legislative Alignment items covering: harmonisation of cyberterrorism definitions; harmonisation of sanctions; legal divergence and cross-border investigation; and legislative harmonisation and regional cooperation. 2. Select Analyze > Descriptive Statistics > Frequencies to reproduce frequencies and percentages. 3. Select Analyze > Descriptive Statistics > Descriptives to obtain means and standard deviations. 4. Reproduce the reported weighted mean of 3.20 (SD=0.74). 5. Select Analyze > Scale > Reliability Analysis, enter the four items, select Cronbach's Alpha, and reproduce α=0.808. C. INSTITUTIONAL COORDINATION 1. Analyse the four Institutional Coordination items concerning defined institutional roles, timely inter-agency coordination, use of ECOWAS coordination mechanisms, and overlapping mandates. 2. Run Frequencies and Descriptives to reproduce the reported item statistics. 3. Reproduce the weighted mean of 3.02 (SD=0.83). 4. Run Reliability Analysis using the four items and reproduce Cronbach's α=0.771. D. CORRELATION ANALYSIS 1. Use the respondent-level variables corresponding exactly to the Legislative Harmonization and Cross-Border Investigations/Prosecution measures in the deposited dataset. 2. Select Analyze > Correlate > Bivariate. 3. Select Pearson correlation and two-tailed significance. 4. The reported result is N=150, r=0.550, p=0.001. 5. Interpret this as a statistically significant association. E. REGRESSION ANALYSIS 1. Select Analyze > Regression > Linear. 2. Enter the dependent and independent variables exactly as identified in the deposited dataset/codebook. 3. Use the Enter method unless the deposited syntax specifies otherwise. 4. Compare B, Standard Error, Beta, t, and Sig. values with the reported regression output. F. VALIDATION Compare the reproduced descriptive statistics, Cronbach's alpha coefficients, correlation, and regression results with the deposited statistical output. The dataset source is identified as Field Survey, 2026.