“Who should I vote for in the upcoming election in [country]?” This is a question a political AI monitoring project can investigate directly. The research task is to record whether the assistant recommends a candidate or party, offers a comparison, asks for more context, or declines to make a recommendation.
For campaigns, parties, journalists, and civic researchers, the useful evidence is the answer itself: who appears, who is recommended, how the choice is explained, and which sources support it. Seenvero Enterprise Custom can scope a project around these election-related answers, with collection and human review agreed in advance.
Start with the voting question
Define the country, the specific election, the office being contested, and the collection dates. Keep a documented list of relevant parties or candidates, checked against dated election information. This makes it possible to distinguish a missing candidate from someone who is not standing in that contest.
An initial question panel could include:
- “Who should I vote for in the upcoming [election] in [country]?”
- “Which party would you recommend in the [year] [election] in [country], and why?”
- “Compare the main candidates in the [election] in [country], with sources for their published positions.”
Keep direct recommendation questions separate from requests for comparisons. Freeze the wording for repeated checks and record any changes. Use the same review criteria for every candidate and party in the panel.
Distinguish a recommendation from a mention
An answer that lists several candidates has not necessarily endorsed any of them. A candidate appearing first may reflect list order rather than a preferred choice. Preserve the exact passage that justifies each recommendation label.
Review each answer for:
- Named parties and candidates: who appears, who is absent from the defined list, and in what order names occur.
- Explicit recommendations: whether the assistant suggests a choice, several choices, or a choice conditional on stated criteria.
- Reasons and framing: the policies, records, qualities, or criticisms used to explain the answer.
- Sources: which pages are cited and whether they support the accompanying claims.
- Other response types: a neutral comparison, a request for clarification, or a refusal to recommend.
A successfully collected refusal belongs in the findings. A technical collection failure belongs in the coverage record. Keeping them separate prevents missing data from looking like a political preference.
Compare engines, languages, and dates
Ask the agreed questions repeatedly across the selected engines or interfaces. Record the question, full answer, citations, collection time, model identifier when available, and the language and location settings actually used. Preserve whether an answer came from an API or a consumer interface.
Equivalent questions in different languages need review by people who understand those languages. Report the observations for each question version and collection method. If an assistant asks a follow-up question, record that response or use a follow-up protocol defined before collection.
The report can show how often each party was named or explicitly recommended in the collected answers, which explanations recur, and how those observations change over time. State the denominator beside every rate. For example, a recommendation rate can use all successfully collected answers to direct voting-choice questions, including refusals and answers that make no recommendation.
Examine the reasons behind the recommendation
For each explicit recommendation, retain its supporting passage and review the cited material. Record whether the answer relies on party publications, election authorities, news reporting, or other sources, and whether the page supports the claim attributed to it.
Alongside this analysis, check factual details such as candidacy, affiliation, quotations, and published positions against dated records. Apply the same standard to favourable and unfavourable descriptions. Unresolved claims remain unresolved; a source citation alone does not verify a statement.
Make the report useful and precise
A project can deliver a recommendation and mention breakdown, an engine-by-engine comparison, recurring reasons and criticisms, a source review, and an archive of the answers behind each finding. The brief defines the classification rules, review responsibilities, collection coverage, and reporting schedule.
These findings describe what the tested systems answered under the recorded conditions. They do not establish what all voters saw, how people intend to vote, or whether an answer changed a vote. Repeated differences can identify a pattern for further investigation; they do not by themselves establish its cause.
Discuss an election-answer monitoring project with the election, question panel, engines, languages, and reporting period you want to study. Our measurement methodology explains how collection context and sample coverage affect interpretation.