How to monitor election disinformation: a task checklist for the 60 days before the election
The monitoring checklist in this article covers voting and vote-counting procedures, candidate statements, polls and audio-video content. The closer to polling day, the shorter the time for verification and clarification, so the division of labor and response methods should be settled before the election. This article uses Taiwan's 2026 local elections as an example to organize the operational checklist, which can also be adapted for later elections at all levels.
Quick answer: how do you monitor election disinformation?
Election disinformation monitoring is the practice of continuously collecting public content from news, social media, forums and public messaging-app communities during an election, identifying suspicious claims related to voting and counting procedures, candidates, polls and deepfake audio and video, flagging suspicious leads, and then handing them to people for verification. Before the election, you can confirm the topics and public sources to watch, the division of labor for human verification, and how clarifications will be published; the closer to polling day, the less time there is for verification. What the tools produce is suspicious signals; whether something is true or false, and how to respond, is decided by people.
Who it is for
- Central and local election authorities: helping spot suspicious claims about voting and vote-counting information for people to check
- Local governments: handle claims awaiting verification that are driven by the election and concern public services within their jurisdiction
- Campaign teams of any camp: spot suspected forged content targeting their own candidate early
- Media and fact-checkers: build a list of claims awaiting verification and find where a claim first appears in the currently observable data
Five categories of suspicious information to monitor during an election
In their 2017 report Information Disorder, written for the Council of Europe, Wardle and Derakhshan divided information disorder into misinformation, disinformation and malinformation. In monitoring practice you do not need to decide first which kind something is; this article uses five categories by content type, because each category has different responders and verification methods. Everything in the table is content awaiting verification and does not mean it has been confirmed false.
| What to monitor | Typical patterns | Observable signals | Primary responders |
|---|---|---|---|
| Voting and vote-counting procedures | Voting dates, locations or ID requirements that differ from official announcements, or claims that a certain way of marking the ballot makes it invalid | Keyword combinations inconsistent with official announcements; the same graphic appearing on multiple social platforms at the same time | Election authorities |
| Candidate-related statements | Suspected forged screenshots of remarks, quotations taken out of context, impersonated official accounts or campaign materials | Text in images that does not match the original source; new accounts posting in bursts; similar posts appearing in sync | The candidate camps and media concerned |
| Poll-related content | Poll graphics of unknown origin or in the name of impersonated organizations; poll data circulating during the blackout period | Original data with no identifiable publisher; graphics reposted across platforms within a short time | Election authorities, media |
| Suspected deepfake audio and video | Voice or video clips of candidates suspected of being synthesized or altered | Suspicious signals from video and deepfake detection; characteristics of the posting account; mismatch with the person's existing public footage | The candidate camps and fact-checking organizations concerned |
| Post-election claims about results | Factual statements about vote counting or results that need verification, or old footage relabeled with a new time and place | Abnormal volume during the vote-counting period; old images or videos reappearing with new captions | Election authorities, local governments |
The key is in the right column. For claims about voting procedures and results, we recommend that election authorities fact-check first; for candidate and audio-video content, the camps concerned can provide original materials and responses. Poll-related content should be recorded separately: dissemination during the blackout period concerns publication rules, which is a separate matter from whether the content is true. Criticism of election administration or results is normal speech; what needs verification are the unconfirmed factual statements within it.
Who needs monitoring: different goals, different boundaries
A monitoring plan should explicitly list the monitoring targets, verification scope and response responsibilities of each user.
| User | Monitoring focus | Boundaries to observe |
|---|---|---|
| Election authorities | Claims about voting and vote-counting procedures; announcements issued in the name of impersonated agencies | Clarify only procedural facts, and take no position on candidates, parties or policy platforms |
| Local governments | Claims needing verification that are driven by the election and concern public services within the jurisdiction | Maintain administrative neutrality; limit responses to verifiable facts within the agency's remit |
| Campaign teams | Suspected forged screenshots, fake quotes, impersonation accounts and deepfake audio and video targeting their own candidate | Used only to identify and clarify forged content, not to track or label critics |
| Media and fact-checkers | The earliest position, spread range and variants of a claim awaiting fact-checking within the currently observable data | When reporting, avoid reproducing the original text or audio and video in full, to reduce secondary spread |
Neutrality means that what gets monitored is determined by content type, not by political position. For content involving identifiable individuals, first confirm the legal basis and necessary scope for collecting, processing and using personal data. Taiwan already has several fact-checking organizations and civic collaborative verification communities, and their published fact-check results can be added to the comparison list, but fact-check results should also be confirmed against the original sources.
Checklist: from 60 days before the election to after the count
The checklist below is divided into five phases by time and lists what to consider at each phase. These are general starting suggestions; the actual scope, frequency and division of labor should be decided by each organization according to its remit, data availability and staffing.
| Phase | Things to consider | Points to note |
|---|---|---|
| 60 days before the election | Confirm the topics and public sources to watch, such as election authority notices, official accounts of candidates and parties, and local communities and forums; include abbreviations, homophones and common misspellings in keywords; first observe normal discussion volume as a reference for later comparison | Monitoring covers only public content that can be obtained; normal discussion volume shifts with the topic and should not be treated as a fixed standard |
| 30 days before the election | Compile published fact-check results so recurring claims can be compared; watch for different variants of the same claim; confirm the legal requirements for the poll blackout period | The same claim may reappear in different wording, so compare on the substance of the claim, not the literal text |
| 7 days before the election | Compile accurate information on voting and vote-counting procedures from election authority announcements, for comparison during verification; review the causes of earlier misjudgments | Less time is available for verification, so monitoring scope can be reassessed according to data availability and staffing |
| Election day | Watch for suspicious claims about voting and vote-counting procedures and pass them to people for verification; keep the sources on which each judgment was based | Procedural claims may surge within a short time, so keep verification and clarification timely; clarifications address procedural facts only |
| After the count | Watch for claims needing verification about vote counting or results, and for old footage relabeled with a new time and place; retain or delete data as required | Criticism of results is normal speech; what needs verification are the unconfirmed factual statements within it |
Taking Taiwan's 2026 local elections as an example, the election announcement was issued on August 20, and election day is November 28. If you have less than 60 days to prepare, you can merge the first two phases and start by confirming topics, public sources and the division of labor for human verification; keywords can be added as you go.
Ordering verification: factors to consider
When there are many suspicious leads, you need to decide which to check first. Common considerations include whether the content is a specific factual statement, such as the voting date, location or how to mark the ballot; whether it has already appeared on multiple platforms; and, if it is false, how wide its potential impact could be. There is no universal standard for weighting these factors; each organization should decide according to its remit and staffing, and people should assess each case on the evidence.
Spread metrics reflect observable propagation; they are not the same as actual exposure and cannot be used to judge truth. Even when a suspected deepfake video has few reposts, it is advisable to first preserve the earliest version obtained and then pass it to people for verification; content with many reposts may also be genuine material.
Deepfake audio and video: a category that needs planning in advance
Deepfake audio and video deserve separate planning, for three reasons. First, when the Civil Servants Election and Recall Act was amended in 2023, Article 104, paragraph 2 was added: a person who commits the offense in paragraph 1 by disseminating, broadcasting or otherwise making available for viewing deepfake audio, images or electromagnetic records of the candidate, the person subject to recall, or the lead proposer of a recall in person is punishable by imprisonment of up to seven years. Second, video can be reposted across platforms and is hard to catch with text keywords. Third, verification may require the original file and expertise in audio and video analysis.
| Step | What you can do | Limits and human verification |
|---|---|---|
| Discovery | Beyond text keywords, watch for related claims in video titles, descriptions and comments; monitoring tools can help flag suspicious leads | Actual coverage depends on data availability; confirm the earliest position and version in the currently observable data |
| First screening | Detection tools can produce suspicious signals, with on-screen text and image comparison as support | Judge whether it is synthesized or altered; detection results are not a forensic conclusion |
| Tracing the source | Compile observable publication times and repost context | Compare against public schedules and original footage, and confirm with the person concerned |
| Preservation | Preserve the earliest version obtained and its source | Where legal proceedings are involved, separately confirm how to preserve and forensically examine the material |
Two reminders. First, after lossy recompression a video may lose picture or audio quality, which affects judgment, so keep the earliest version you obtained. Second, the deepfake problem cuts both ways: a forged video may be taken as real, and a real video may be claimed to be fake; in both cases go back to the original material and confirm with the person concerned.
How to read the metrics: four extra reading tips from a disinformation angle
The three basic misuses of volume, sentiment ratios and anomaly signals are covered in the article “Election sentiment analysis and public opinion tracking”. Below are four more reading tips related to verifying suspicious information.
| What is observed | The wrong conclusion that is easy to draw | A more reasonable reading |
|---|---|---|
| Related volume rises after a clarification is published | The original claim is still spreading and the clarification is ineffective | Count the original claim and the clarification discussion separately; what is rising may be reposts of the clarification |
| A claim has very low volume on the major platforms | Impact is limited and no action is needed | It may already be circulating in messaging-app communities or short-video platforms; check the time lag between platforms |
| A group of accounts post the same slogan at the same time | This is coordinated inauthentic behavior | Simultaneous posting is not enough to prove coordinated inauthentic behavior; you still need to check account identity, source disclosure and content |
| Deepfake detection gives a high suspicion score | The video is definitely forged | This is the starting point for verification; a low score does not mean it is genuine either, and in both cases go back to the original material |
The third row needs an explanation of the criterion. In its 2020 CIB report, Facebook, Inc. (now Meta Platforms) defined coordinated inauthentic behavior as coordinated manipulation of public debate for a strategic goal, with fake accounts at the core of the operation; enforcement is based on the deceptive nature of the behavior, not on the content itself. So you cannot conclude such behavior from simultaneous posting alone; and being publicly named does not make the content correct, as factual statements can still be verified through the usual process. Identifying coordination and anomalous accounts is a probabilistic assessment that can produce misjudgments and requires human review.
Another common type of reference material is public volume dashboards or trend tools, which can show changes in discussion volume for a region or topic. Such data works well as background: when a suspicious claim appears, check whether related discussion was already heating up, to judge whether the claim rode on an existing topic or appeared suddenly while discussion was quiet. But volume is not a poll: you cannot infer vote shares or election results from high or low volume alone, nor judge from it whether a message is true; different tools differ in data sources and coverage, so confirm how each one measures before comparing.
2026 Taiwan Election Lab: use public volume as a background reference
The dashboard built by LargitData with InfoMiner, called “2026 Taiwan Election Lab”, is a public volume dashboard covering all 22 counties and cities in Taiwan. It is not a poll, does not predict results and does not judge whether a message is true.
Legal reminders: spreading rumors, deepfakes and the poll blackout
The directly relevant current provisions are mainly in the Civil Servants Election and Recall Act. The table below summarizes the key points of each provision and what they mean for monitoring.
| Provision | Key points | What it means for monitoring |
|---|---|---|
| Article 104, paragraph 1 | A person who, intending to cause a candidate to be elected or not elected, or a recall to pass or fail, spreads rumors or disseminates false matters that are sufficient to harm the public or others, is punishable by imprisonment of up to five years | Monitoring can only flag claims that need verification; whether this offense has been committed must be determined by the competent authority according to law |
| Article 104, paragraph 2 | Added in 2023: a person who commits the offense in the preceding paragraph by disseminating, broadcasting or otherwise making available for viewing deepfake audio, images or electromagnetic records of the candidate, the person subject to recall, or the lead proposer of the recall in person is punishable by imprisonment of up to seven years | For suspected deepfake audio and video, preserve the earliest original file obtained as a priority; whether it is genuine must be verified by people |
| Article 53, paragraph 3 | From ten days before election day until voting closes, political parties and any person may not publish, report, disseminate, comment on or quote in any way the material covered by the first two paragraphs of the same article, namely poll data about candidates, persons subject to recall, or elections or recalls, and other election or recall material that has the appearance of a poll | Such material is something to monitor, and what is recorded is the act of publishing, separate from whether the content is true; your own outward-facing reports must be checked too |
Monitoring itself also has boundaries: collection is limited to public content, the unit of analysis is topics and spread patterns, profiling of individuals beyond the purpose is avoided, and legal requirements such as personal data protection are assessed according to the use; criticism, satire and expression of opinion are not targets for action. Whether content is true is judged by fact-checkers on the evidence; whether something is illegal is determined by the competent authority according to law, and being judged false does not mean being illegal. The provisions are as currently published in the Laws and Regulations Database of the Republic of China and in election authority announcements.
Further Reading
- Fake News Detection and Cognitive Warfare Monitoring System
- What is cognitive warfare? How it differs from fake news, information manipulation and FIMI
- How does AI detect fake news? Five methods and what they cannot do
- Election sentiment analysis and public opinion tracking
- Social listening crisis handling SOP: a 7-step guide to PR crises
- Critical Infrastructure and Public Sector Intelligence
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