eMonitor+ flags violent posts aimed at Libya's women politicians

UNDP's evaluation office found that Libya's election commission now uses eMonitor+, which flags violent content directed at women politicians, to respond with targeted communications.

  • Not rated an organization

    The office found that the commission uses the tool's flags to respond, but it gives no count of flags, responses or effects.

  • Not rated society

    No change in online violence against women politicians or in their participation is measured.

Depth runs from 1, a convenience or time saved, to 5, a life or a livelihood preserved.

Status
Reported benefit.
Evidence

foundstudiedreportedclaimed

Two independent evaluation reports support the benefit.

The system’s part
Not isolated. The office states that eMonitor+ employs artificial intelligence to flag violent content, and UNDP writes in a release that it uses machine learning. Neither the office nor UNDP describes the model, its accuracy or how many flags led to a response. The AI's part therefore cannot be separated from the commission's own work.
Limits
Not yet checked.
Costs and harms
Not yet checked.
Later
Not yet checked.

Download data Cite Suggest a correction

Benefit type
Reduced Risk
System
eMonitor+, UNDP's platform for monitoring online media
Made by
UNDP Regional Bureau for Arab States
Used by
High National Elections Commission (HNEC), Libya, with UNDP and the UN Support Mission in Libya
Where
Libya
Stage
In routine use
Date
, when the source was published
Kind
Protective response
Broad benefit
Identifying Objects, Actions, and Events, Monitoring Processes, Materials, or Surroundings
Collections
Scrutiny and findings, Safeguards
Last revised
31 October 2026

Sources

  1. Evaluation report, by authors with no tie to the system.

    UNDP Independent Evaluation Office. Independent Country Programme Evaluation: Libya. December 2025, Chapter 2 (Findings). The evaluation team visited Libya in November 2024.

    The HNEC now uses the eMonitor+ tool, which employs artificial intelligence to flag violent content directed to women politicians, allowing it to respond with targeted communications.

  2. Evaluation report, by authors with no tie to the system.

    UNDP Independent Evaluation Office. Evaluation of the UNDP Support to Digitalization of Public Services. November 2023. The report is an independent publication of the office. Section on electoral support.

    In Libya, data was collected to understand the causes of electoral harassment and violence and to identify solutions, especially to enhance women's participation, and support the election commission in developing strategies, procedures and activities that reached out to women.

  3. Press release, by the makers. Context or contrary evidence.

    UNDP Regional Bureau for Arab States. Election Commission uses artificial intelligent to enhance women's participation in electoral processes. Press release, Tripoli, 9 August 2022, note to editors (archived copy). UNDP's Regional Bureau for Arab States developed eMonitor+.

    It relies on machine learning to track and analyze the content on digital media to generate graphical representations for data visualization.

Details

AI system

Workflow

UNDP supported the creation of a Women Support Unit in the commission in 2022. The unit launched eMonitor+ to combat online violence against women candidates. Media monitors were trained to use the platform in August 2022.

Follow-up

Conditions for replication

The platform must work in Arabic, one of its four languages. The commission must turn flags into targeted communications and outreach to women.

Entry details

Sector

Electoral integrity / online violence against women.

Purpose

UNDP's Regional Bureau for Arab States built eMonitor+ to scan online media for electoral violations, hate speech and online violence against women.

Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, AI contribution, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.

Cite this record

Peter H. Vartanian. (2026). eMonitor+ flags violent posts aimed at Libya's women politicians (AIBD-0693). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0693.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)

BibTeX Data Field definitions