INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)

ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025

Developing a Community-Based Election Monitoring and

Whistleblowing Framework to Combat Electoral Malpractices in the

South-South Geopolitical Zone, Nigeria

Ademola Oyeleye Oyebanji¹, Lydia Alicha John², Bulus Simon³

¹Department of Pubic Administration, Federal Polytechnic, Ukana

²Department of Environmental Science and Management Technology, Federal Polytechnic, Ukana

³Department of General Studies, Federal Polytechnic, Ukana

DOI: https://dx.doi.org/10.51244/IJRSI.2025.1210000362

Received: 02 November 2025; Accepted: 12 November 2025; Published: 25 November 2025

ABSTRACT

Electoral malpractice continues to hinder democratic consolidation in Nigeria, particularly in the South-South

region where citizen oversight is weak. This study developed a Community-Based Election Monitoring and

Whistleblowing Framework (CEMWF) to strengthen transparency and accountability during elections. A mixed-

method approach was employed, combining quantitative surveys of 432 respondents across Akwa Ibom, Rivers,

and Delta States with qualitative interviews and focus group discussions. Quantitative data were analyzed using

weighted descriptive statistics, chi-square tests, logistic regression, and difference-in-differences (DID) analysis,

while spatial hotspot mapping and thematic coding complemented the results. Findings showed that 48.3% of

respondents experienced electoral malpractice, but only 26.4% reported it, citing low institutional trust (mean =

2.7/5) and a strong preference for anonymity (mean = 4.7/5). Smartphone ownership (71.7%) and internet access

(65.2%) demonstrated readiness for digital monitoring. Reporting likelihood increased with incident severity

(OR = 1.80, p < 0.001) and smartphone ownership (OR = 2.30, p = 0.004), while anonymity concerns

discouraged reporting. They DID results showed a 3.5-point reduction (p = 0.010) in verified malpractices post-

intervention. The study concludes that community-driven, blockchain-enabled monitoring can enhance electoral

integrity and rebuild citizen trust in governance.

Keywords: Blockchain, community monitoring, democratic governance, electoral malpractice, whistleblowing.

INTRODUCTION

Free, fair and transparent elections are the cornerstone of democratic governance because they provide citizens

with a credible mechanism for selecting leaders and holding them accountable. Yet, across many contexts,

electoral integrity is undermined by malpractice including vote buying, intimidation, ballot tampering, and result

manipulation which erodes public trust, depresses turnout, and weakens democratic consolidation

(Onwuharaonye, Ebere & Abaneme, 2024). At the international level, scholars emphasise that strengthening

monitoring, improving evidence trails and building community engagement are central to restoring confidence

in electoral processes (Ezeador, 2023). In sub-Saharan Africa, and particularly in Nigeria, electoral malpractice

remains a persistent problem despite incremental administrative reforms. Empirical reports and policy reviews

of recent election cycles document how vote-buying, ballot-box irregularities, and localized violence continue

to distort outcomes and weaken the legitimacy of elected authorities (Ezeabasili, 2024; Amaec hina et al., 2024).

Civil society organisations (CSOs) have played a central role in observation and advocacy, yet their capacity

and reach are uneven and sometimes constrained by legal, logistical and security challenges (Nwagwu et al.,

2024).

The South-South geopolitical zone of Nigeria (including Akwa Ibom, Rivers and Delta states) is of particular

interest because oil-related politics, urban-riverine population patterns and intense local competition create

conditions conducive to multiple forms of malpractice. Empirical reports of vote-buying and result manipulation

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in the region underscore the need for localized, context-sensitive monitoring that combines grassroots knowledge

with robust evidentiary systems. These localized dynamics mean that national, one-size-fits-all approaches to

monitoring often miss hotspots and fail to deliver timely, verifiable evidence for corrective action. Technological

solutions including mobile reporting platforms, geotagged evidence collection, and distributed ledgers

(blockchain) have been proposed as ways to secure evidence, improve transparency and reduce opportunities for

manipulation. Recent applied studies suggest that permissioned blockchain systems can ensure immutability of

reports while hybrid front-ends (USSD, mobile app, WhatsApp) improve accessibility for low-bandwidth

contexts (Isibor, 2023). However, technology on its own does not solve the political and social barriers: citizens'

willingness to report is shaped by trust, perceived retaliation risk, and the existence of credible verification and

follow-up mechanisms (Ikuero et al., 2021). A closer look at the literature reveals three gaps that motivate this

study. First, most empirical work on technology for elections in Nigeria focuses on theoretical feasibility or

narrow pilot implementations; few studies combine community-level social processes with secure evidence

architectures and evaluate the combined effect on verified malpractice rates. Second, there is limited high-quality

quantitative evidence linking digital readiness (smartphone and internet access), anonymity preferences, and

actual reporting behaviour in hotspot regions such as the South-South. Third, where pilot technical systems have

been tested, rigorous impact evaluation (for example, difference-in-differences using matched control LGAs)

and spatial hotspot analyses are rarely applied together to show whether technology + community approaches

reduce verified incidents at the polling-unit level. These gaps leave policymakers with promising ideas but little

robust evidence on what works at scale and in highly contested sub-national contexts.

This study addresses these gaps by developing and empirically testing a Community-Based Election Monitoring

and Whistleblowing Framework (CEMWF) for the South-South region. The framework pairs community

monitoring cells and CSO verification hubs with a permissioned blockchain ledger for immutable report

tracking, and flexible front-end channels (mobile app, WhatsApp, USSD) to accommodate diverse connectivity

contexts. Using a convergent mixed-methods design, the research measures (1) the prevalence and reporting

behaviour of malpractice, (2) the relationship between digital readiness, trust and reporting, and (3) the causal

impact of deploying the CEMWF on verified malpractice rates using difference-in-differences estimation and

spatial hotspot analysis. By combining social and technical interventions and subjecting them to rigorous

quantitative and qualitative evaluation, the study provides policy-relevant evidence on whether and how

community-driven, blockchain-enabled monitoring can improve electoral integrity in Nigeria.

STUDY AREA

The study was conducted in the South-South geopolitical zone of Nigeria, one of the country’s six geopolitical

regions. The zone is composed of six states Akwa Ibom, Rivers, Delta, Bayelsa, Cross River, and Edo but this

study focused on Akwa Ibom, Rivers, and Delta States, which are among the most politically active and

demographically significant in the region. The area is characterized by a high level of political engagement,

frequent electoral disputes, and varying degrees of electoral violence, making it a critical setting for assessing

community-based mechanisms for election monitoring and whistleblowing. Geographically, the South-South

zone lies between latitudes 4°15′N and 6°30′N and longitudes 5°00′E and 8°30′E, covering an area dominated

by the Niger Delta Basin. The region’s terrain consists largely of low-lying coastal plains, creeks, and mangrove

swamps, with inland areas featuring forest zones and farmlands. The climate is typically tropical, with high

rainfall and humidity that often pose logistical challenges during electoral processes, particularly in rural and

riverine communities (Akinola, 2019). Akwa Ibom State, with a population of 2,357,418, is located in the

southeastern part of the Niger Delta and is known for its dense population, high literacy rate, and vibrant civil

society. Rivers State, with a population of 3,537,190, serves as the economic hub of the region, hosting the city

of Port Harcourt, a center for oil and gas operations and intense political competition. Delta State, with a

population of 3,221,697, is ethnically diverse and politically dynamic, with a history of grassroots mobilization

and strong community-based organizations that influence local governance (Ibeanu & Orji, 2020).

MATERIALS AND METHODS

This study adopted a mixed-method research design integrating quantitative and qualitative techniques to

develop and empirically test a Community-Based Election Monitoring and Whistleblowing Framework

(CEMWF) for addressing electoral malpractices in the South-South geopolitical zone of Nigeria. The study was

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conducted across Akwa Ibom, Rivers, and Delta States areas selected purposively because they have historically

recorded high incidences of electoral irregularities, dense voter populations, and increasing adoption of digital

technologies during elections. The target population consisted of registered voters, civil society actors, and

community-based election observers, representing a combined population of 9,116,305 across the three states

(Akwa Ibom: 2,357,418; Rivers: 3,537,190; Delta: 3,221,697). The sample size was determined using Yamane's

(1967) formula at a 5% precision level, resulting in 432 respondents. The sample was proportionally allocated

according to state population: Akwa Ibom (112), Rivers (168), and Delta (152). A multistage sampling technique

was adopted to ensure fair representation. At Stage 1, the three states were selected purposively based on

electoral sensitivity. At Stage 2, local government areas (LGAs) within each state were stratified into urban,

semi-urban, and rural categories, from which LGAs were randomly selected. At Stage 3, polling units (PUs)

within selected LGAs were arranged using the official INEC register, and voters were chosen using a systematic

random sampling method, selecting every kth eligible participant. Respondents for key informant interviews

(KIIs) and focus group discussions (FGDs) were selected through purposive sampling, targeting electoral

officers, NGO representatives, youth leaders, and community monitors who possessed firsthand knowledge of

election processes.

The study utilised three instruments: a structured questionnaire, an FGD guide, and a KII protocol. The

questionnaire covered demographic characteristics, experiences of malpractice, whistleblowing behaviours,

digital readiness, and perceptions of institutional trust. To ensure content validity, the instruments were reviewed

by three experts in political science, public policy, and measurement/evaluation. A pilot test involving 35

respondents (not included in the main study) was conducted in Uyo, yielding a Cronbach's alpha coefficient of

0.82, confirming internal consistency and reliability. Data were collected in clearly defined steps to ensure

transparency and replicability. First, field assistants were trained on ethical protocols, sampling procedures, and

administration techniques. Second, questionnaires were physically administered at selected PUs during non-

election periods to avoid interference with electoral processes. Third, KIIs and FGDs were conducted in neutral

community centres, recorded with consent, and transcribed verbatim. Safeguards were observed to maintain

confidentiality, voluntary participation, and anonymity. Quantitative data were analyzed using SPSS 26 and

STATA 17. Weighted descriptive statistics were applied to adjust for differential state populations. Bivariate

relationships were examined using chi-square tests, while predictors of whistleblowing behaviour were assessed

through logistic regression analysis. The effectiveness of the prototype CEMWF system was evaluated using the

Difference-in-Differences (DID) technique comparing intervention and control LGAs before and after system

introduction. Qualitative data from KIIs and FGDs were analysed through thematic coding in NVivo, and results

were triangulated with quantitative findings to enhance depth, contextual accuracy, and methodological

robustness.

RESULTS

Table 3.1: Demographic Characteristics of Respondents (n = 432)

Variable

Akwa Ibom Rivers

Delta

(n=162)

South-South

Mean / %

(n=108)

(n=162)

48.2

51.6

49.7

35.7

44.8

37.8

71.1

65.4

49.8

34.8

44.9

37.4

71.7

65.2

Sex (% Male)

34.9

33.8

Mean Age (Years)

42.6

47.2

Education Level (% Tertiary)

Occupation (% Self-employed)

Smartphone Ownership (% Yes)

Regular Internet Access (% Yes)

35.1

39.3

69.4

74.6

61.8

68.3

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92.4

95.7

5.8

95.1

96.2

4.9

94.3

95.8

5.1

93.9

95.9

5.3

—

Voter Registration (% Yes)

Assigned Polling Unit (% Yes)

Average GPS Accuracy (m)

Historical Contest Level (coded)

Media Reporting (Election Period)

Medium

288

High

461

High

372

—

Source: Field Survey (2025)

Table 3.2: Awareness, Perception, and Trust in Institutions

Variable Akwa Ibom Rivers Delta Regional Mean / %

Knowledge about Election Monitoring 69.7

Systems (% Yes)

76.4

71.2

72.4

Confidence in Institutions (INEC, Police, 2.8

2.5

2.7

Courts) (Mean Likert 1–5)

Perceived Frequency of Electoral 46.9

Malpractices (% Often/Always)

53.6

4.8

48.2

4.7

49.6

4.7

Anonymity Importance (Likert 1 to 5)

Source: Field Survey (2025)

4.6

Table 4.3: Experience with Electoral Malpractices (Incidence Reporting Summary).

Variable

Akwa Ibom Rivers

Delta

Regional

Mean / %

42.3

54.7

47.9

48.3

Ever Experienced Malpractice (%

Yes)

Vote Buying Intimidation/

Violence

Collusion

—

Dominant Incident Type

3.4

3.8

3.6

Average Severity (1–5)

Perpetrator Type (% Party Agents)

45.5

50.3

28.7

48.2

26.1

48.0

26.4

Reported

Incidents

(%)

of 24.5

Experience)

Favorite reporting Channel

Mobile App

8.9

9.7

—

10.8

31.5

9.8

33.7

Avg. Response Time (hrs)

35.7

33.8

Outcome of Reports (% Follow-

up)

Source: Field Survey (2025)

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Table 4.3 revealed that, nearly half of the respondents (48.3%) had experienced electoral malpractice confirms

the persistence of irregularities such as vote buying, intimidation, and manipulation that continue to undermine

electoral integrity in Nigeria. This pattern echoes prior empirical observations by Omotola (2010), who argued

that electoral fraud remains one of the central challenges to Nigeria’s democratic consolidation. Similarly,

Agbaje and Adejumobi (2006) emphasized that systemic malpractices erode citizen trust and political legitimacy.

The relatively low proportion of respondents who reported malpractice (26.4%) further reflects a civic

disengagement driven by fear and mistrust of institutions, aligning with the findings of Nwokedi (2021) that fear

of retaliation discourages public reporting.

Table 4.4: ICT and Digital Readiness Indicators

Variable

Akwa Ibom

69.4

Rivers Delta Regional Mean / %

74.6

68.3

2.3

71.1 71.7

65.4 65.2

Smartphone Owner (% Yes)

Regular Internet Access (% Yes)

Average SIM Cards Owned

61.8

2.0

2.2

78.3

84.1

80.9 81.1

Preferred Language for Reporting

(% English)

8.1

9.6

8.9

Avg. Power Supply (hours/day)

57.8

66.4

61.9 62.0

Network Strength (Self-rated: %

Good)

Source: Field Survey (2025)

Table 4.4 revealed that, 71.7% of respondents owned smartphones and 65.2% had regular internet access,

suggesting moderate digital readiness across the South-South region. These results correspond with Adebayo

(2022), who found that the proliferation of mobile technology in Nigeria creates new opportunities for digital

participation and election transparency. The statistically significant association between smartphone ownership

and reporting (χ² = 10.50, p = 0.0012; OR = 2.30) confirms that technology access enhances the likelihood of

citizens reporting electoral misconduct. Similar outcomes were documented by Ezeani and Igwe (2020), who

demonstrated that digital tools can improve information flow and accountability in electoral processes.

Table 4.5: Polling Unit Observations (n = 81 PUs)

Observation Parameter

% Observed Regional Remarks

83.7

91.1

65.3

39.5

93.2

13.8

Predominantly police; low military visibility

Security Presence (Yes)

8.9% found tampered before closing

Urban centers better organized than rural PUs

Higher in Rivers and Delta

Ballot Box Condition (Sealed)

Queue Behaviour (Orderly)

Observed Vote Buying

Nearly all polling units had at least one party agent

Mostly in remote riverine wards

Party Agent Presence

Logistical Failure (Missing Materials)

Source: Field Survey (2025)

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Table 4.6: Report Verification and Blockchain System Metrics (Pilot Test)

Metric

Mean / Total Performance Remarks

198

During the pilot in three states

Cumulative Reports Made

Verified Reports

138 (69.7%) Dual-source verification was done.

19 (9.6%)

5.8 hours

Flagged through AI–human validation

False Reports

Met 12-hour response threshold

Avg. Time to Verification

Average Blockchain Confirmation Time

Avg. Gas Fee Equivalent

Confirmation Status (Success %)

Report Anonymity Compliance

Average Evidence Attachments on a Report

19.5 seconds Stable among test nodes

₦4.95

99.0

Low transaction cost per report

High system reliability

100%

1.8

All hashes stored without PII

Mix of images and short clips

Source: Field Survey (2025)

Table 4.7: Organizational Performance Indicators (INEC/CSO Monitoring)

Indicator

Baseline

(2023)

After

(2025)

Pilot % Change / Comment

28

126

+350% increase due to tech

integration

Total Reports collected (per day)

25.8

23.4

10.1

6.1

−76% improvement

+155% improvement

+314%

Avg. Acknowledgment Time (hrs)

% Escalated to Action

59.7

41.8

% Closed with Administrative

Action

2

11

+450%

Prosecution Count

17.5

27.3

9.6

66.2

−45% reduction

+142% improvement

False Report Rate (%)

Verified Incident Resolution Rate

(%)

Source: Field Survey (2025)

Table 4.8: Summary of Quantitative Results and Model Estimates (n = 432)

Indicator / Metric

Value / Statistic

432

Respondents (pooled)

Experienced malpractice (%)

48.3

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26.4

Reported incidents (%)

71.7

Smartphone ownership (%)

Regular internet access (%)

Mean trust score (1–5)

65.2

2.7

4.7

Mean anonymity importance (1–5)

χ² = 10.50, df = 1, p = 0.0012

Chi-square test (Smartphone

Reporting)

×

Pre = 9.4, Post = 5.6, Change = −3.8

Pre = 8.2, Post = 7.9, Change = −0.3

Intervention LGAs (Pre-Post Change)

Control LGAs (Pre-Post Change)

Top Hotspots (PU-level)

RIV-PHC-W12 (78%), DEL-WAR-PU04 (64%), AKW-EKET-

W03 (56%)

Source: SPPS V25 Analysis, (2025)

Table 4.10: Logistic regression predicting reporting (DV = 1 if reported; n = 209; clustered SEs)

Predictor

Coef (logit) Odds Ratio (OR) 95% CI (OR)

p-value

0.002

<0.001

0.004

0.076

0.012

0.58

Intercept

−3.12

0.587

0.832

0.182

—

Severity (1–5)

Smartphone (1=yes)

Trust score (1–5)

1.80

2.30

1.20

0.70

1.01

1.14

1.35 – 2.41

1.30 – 4.07

0.98 – 1.46

0.53 – 0.92

0.99 – 1.03

0.68 – 1.92

Anonymity importance (1–5) −0.357

Age (years)

0.005

0.128

Sex (male=1)

0.61

Model fit: pseudo-R² (McFadden) = 0.22.

Community-Driven Election Monitoring Framework (Integrated with Technology)

The proposed Community-Based Election Monitoring and Whistleblowing Framework (CEMWF) is a multi-

tiered system that connects grassroots citizen observers, civil society organizations (CSOs), and regulatory

institutions

(INEC,

Police,

EFCC)

through

a

real-time

digital

ecosystem.

The design leverages high smartphone ownership (≈71.7%), increasing digital readiness, and the strong

community structures identified during the baseline survey

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Figure 5.1 Community-Based Election Monitoring and Whistleblowing Framework (CEMWF)

DISCUSSION OF FINDINGS

The findings of this study provide new empirical insights into how digital readiness, anonymity preferences,

trust dynamics, and community participation interact in shaping whistleblowing behaviour during elections in

Nigeria’s South-South region. Although respondents demonstrated relatively high levels of digital access seen

in the 71.7% smartphone ownership and 65.2% regular internet accessthere remained a notable deficit in

institutional trust (mean = 2.7/5). This aligns with Omodia (2011) and Agbo (2023), who previously linked

persistent electoral malpractice and weak accountability structures to declining trust in political institutions. The

present study reinforces these earlier observations by showing that technological readiness alone does not

automatically translate into active citizen oversight. A particularly important finding is the inverse relationship

between anonymity concerns and reporting behaviour (OR = 0.70, p = 0.012). Although anonymity is typically

expected to increase whistleblowing, respondents who rated anonymity as highly important were less likely to

report. This contradicts simplistic assumptions in the whistleblowing literature but is consistent with Adetula

(2019), who argues that in contexts where retaliation is common and whistleblower protection mechanisms lack

credibility, anonymity alone cannot overcome deep-seated fear or distrust. The present study therefore advances

existing knowledge by demonstrating that anonymity functions differently in politically sensitive environments

operating not only as a motivator but also as a marker of distrust.

Furthermore, the Difference-in-Differences (DID) results show a statistically significant reduction in verified

electoral malpractice (−3.5 incidents per 1,000 voters, p = 0.010) in intervention LGAs after the introduction of

the Community-Based Election Monitoring and Whistleblowing Framework (CEMWF). This finding

empirically supports arguments by Nwankwo and Onuoha (2022) that community participation enhances

accountability by strengthening local ownership of electoral processes. It also aligns with Ojo and Oyetunde

(2021), who highlight blockchain’s tamper-proof attributes as instrumental in curbing manipulation, thereby

enhancing trust and transparency in public sector reporting. Through these convergences, this study demonstrates

that combining social embeddedness with secure digital tools produces synergistic benefits greater than either

approach alone. Spatial hotspot analysis further revealed that electoral malpractice remains geographically

uneven, with urban and politically competitive LGAs such as Port Harcourt City, Warri South, and Eket showing

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higher concentrations of incidents. This corroborates Ibrahim and Aremu (2020), who found that high-density

and high-stakes political environments create incentives for electoral actors to strategically target vulnerable

polling units. By confirming these spatial patterns, the present study extends scholarly understanding by offering

high-resolution, PU-level geospatial evidence that malpractice is not randomly distributed but clustered in

predictable locations.

Theoretically, the findings strengthen socio-technological models that argue that transparency reforms succeed

only when technological innovations are embedded within supportive social structures (Adebanwi, 2021). While

technology may offer immutability, scalability, and anonymity, it cannot replace the legitimacy provided by

trusted intermediaries, civic networks, and community surveillance. The current study contributes to this

theoretical conversation by demonstrating that community-based engagement amplifies the effectiveness of

technologies such as blockchain, while also mitigating distrust and enhancing citizen willingness to

report.Although the sample size of 432 provided robust insights across three states, broader geographic coverage,

repeated-cycle monitoring, and longitudinal assessment of CEMWF adoption would further deepen

understanding of long-term institutional uptake and behavioural change.

CONCLUSION

This study demonstrates that electoral malpractice remains widespread in Nigeria’s South-South region, with

nearly half of respondents reporting direct encounters with irregularities. Yet, the persistently low reporting rate

reflects enduring issues of institutional distrust and perceived vulnerability among citizens. Notably, the region’s

high levels of digital readiness provide a strong foundation for technology-enabled election oversight, but trust

gaps hinder full utilization of available tools. The implementation of the Community-Based Election Monitoring

and Whistleblowing Framework (CEMWF) which integrates community mobilization, mobile reporting, and

blockchain verificationnproduced measurable reductions in confirmed electoral malpractice in intervention

LGAs. This result affirms the feasibility and effectiveness of decentralised, transparent, and citizen-driven

monitoring systems in contexts characterized by historical electoral manipulation. The demonstrated impact of

blockchain’s immutability further underscores its potential to reinforce accountability and strengthen public

confidence in electoral processes.

RECOMMENDATIONS

 INEC and the National Orientation Agency should adopt the CEMWF as part of Nigeria’s official

election monitoring infrastructure, ensuring localized and citizen-led data validation during elections.

 Integrate blockchain verification layers into election reporting platforms to guarantee anonymity, data

immutability, and verifiable audit trails.

 Train community focal points, CSOs, and youth volunteers in digital literacy, mobile reporting, and

secure whistleblowing to sustain participatory election monitoring.

 Amend the Electoral Act to formally recognize community-driven, technology-enabled monitoring as

part of accredited electoral observation frameworks.

 Conduct civic education campaigns that emphasize the confidentiality, safety, and civic importance of

anonymous reporting to rebuild public confidence in democratic institution

 Scale the pilot model beyond the South-South to other geopolitical zones, ensuring funding and policy

alignment with e-governance initiatives under the National Digital Economy Policy (2020-2030)

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