Emerging Topic Trend Monitor

Emerging Topic Trend Monitor helps you turn public news momentum into better short-form content decisions. Run a query, receive ranked deduplicated topic clusters and source records, then use the included momentum and change fields to decide what deserves research or production. Configuration comes after the buyer sees the output shape.

Outcome

Find fast-growing topics, narratives, entities, and sentiment shifts from global news coverage so teams can validate and prioritize content opportunities before investing in TikTok production.

Use cases

• Use the Actor when you need find fast-growing topics, narratives, entities, and sentiment shifts from global news coverage so teams can validate and prioritize content opportunities before investing in TikTok production.
• Build workflows around a repeat-use trend intelligence layer rather than a TikTok scraper: normalize GDELT article metadata into topic clusters, deduplicate coverage, calculate momentum and tone changes across time windows, rank entities and locations, and emit delta records suitable for content planning and alerts.
• Designed for TikTok agencies, creator teams, social media strategists, trend researchers, brand marketers, and content-planning platforms.
• Schedule repeat runs: Daily or weekly monitoring of saved queries, with new-cluster detection, momentum changes, source diversification, and historical comparison.
• Feed normalized dataset records into APIs, spreadsheets, databases, automations, or AI/agent workflows.

Quick start

1. Open the Actor input form.
2. Set the filters or query relevant to your workflow.
3. Start with a small maxResults value.
4. Run the Actor and inspect the default dataset before scheduling larger or recurring jobs.

Example input:

{
  "query": "renewable energy",
  "maxResults": 10,
  "timespan": "7d",
  "mode": "artlist"
}

Inputs

• query (string, required) — A keyword, phrase, Boolean expression, or GDELT-supported search query representing the topic to monitor.
• timespan (string, optional) — GDELT timespan such as 1d, 7d, 30d, or 90d. Defaults to 7d.
• maxResults (integer, optional) — Maximum number of article records to retrieve before normalization and deduplication. Defaults to 100.
• language (string, optional) — Optional language filter such as English, Spanish, French, or All.
• country (string, optional) — Optional country or region filter for source coverage.
• previousRunAt (string, optional) — Optional ISO timestamp used by downstream processing to identify newly observed or materially changed records.
• mode (string, optional) — GDELT DOC API response mode. Artlist returns article metadata records.

Output example

The example below is taken from the latest validated local live-source sample when available; otherwise it is derived from the bundled dataset schema.

{
  "id": "https://www.dostor.org/5684843",
  "query": "",
  "title": "وزير الكهرباء يبحث مع « مصدر » الإماراتية تسريع مشروعات الطاقة المتجددة في مصر",
  "url": "https://www.dostor.org/5684843",
  "domain": "dostor.org",
  "sourceCountry": "Egypt",
  "language": "Arabic",
  "publishedAt": "20260829T134500Z",
  "tone": null,
  "themes": [],
  "entities": [],
  "clusterKey": "https://www.dostor.org/5684843",
  "clusterSize": 1,
  "momentumScore": null,
  "changeType": "new",
  "attribution": "Data source: GDELT Project (https://gdeltproject.org/)."
}

Pricing

Store pricing is configured in Apify. The intended primary paid unit is completed trend-monitoring job. Start with a small result limit while validating your workflow, then scale only when the output and economics fit your use case. The README never hard-codes a price that could drift from the live Store configuration.

Source and limitations

• Source: GDELT 2.0 DOC API.
• Licence/terms: GDELT Project Terms of Use; no separate SPDX license stated.
• Reuse condition: GDELT states that its datasets may be used for unlimited and unrestricted academic, commercial, or governmental use and may be redistributed, rehosted, republished, or mirrored, provided that use or redistribution cites the GDELT Project and links to its website. This Actor should return structured metadata, short snippets where available, source URLs, and derived trend signals; it must not imply endorsement or republish full third-party article text, images, logos, or publisher content. No standalone resale or competing-data-product prohibition was found in the GDELT Project Terms of Use. GDELT Cloud terms are different and prohibit redistribution, so this Actor must use the GDELT Project API directly rather than GDELT Cloud.
• Automation condition: Use HTTP GET requests, bounded pagination, caching, deduplication, exponential backoff, and conservative concurrency. The GDELT Project documents the API and open data but does not provide a clearly stated universal request-rate guarantee in the reviewed sources; treat rate limits as UNKNOWN and implement configurable throttling.
• This is a compliant substitute for TikTok public-content collection, not TikTok-native data; it measures public news and media momentum rather than TikTok views, likes, comments, or creator metrics.
• Third-party article headlines, snippets, images, logos, and trademarks may carry publisher-specific rights. Limit outputs to metadata, short permitted fields, source URLs, and derived signals; do not republish full article content.
• GDELT coverage is biased toward indexed online news and may overrepresent English-language, highly covered, or politically salient topics.
• GDELT documentation does not establish a universal guaranteed API rate limit; conservative throttling and monitoring are required.
• The Actor must use the GDELT Project endpoint directly. GDELT Cloud is not an acceptable upstream because its current policy prohibits third-party redistribution without a separate written license.

This Actor does not bypass authentication, rate limits, robots/API policies, licensing conditions, or upstream access controls. Missing upstream values are not invented.

FAQ

Does this use the approved source contract?
Yes. Runtime requests are restricted to the source contract validated by Market Hunter before build.

Can I schedule repeat runs?
Yes, when the source permits automated access. Use conservative schedules and result limits that respect upstream conditions.

Why can some fields be empty or null?
The upstream source may omit fields for particular records. The Actor preserves missing values rather than fabricating data.

Troubleshooting

• If a narrow query returns no rows, loosen filters and retry with a small result limit.
• If the upstream source returns a rate-limit or temporary server error, retry later instead of increasing request pressure.
• If authentication or source identity is required, verify the protected credential/identity configured for the Actor.
• If the upstream response schema changes, report the failed run so the deterministic mapping can be updated.

Related Actors

• brand-mention-trend-monitor
• news-entity-cooccurrence-monitor
• geopolitical-event-monitor
• social-content-keyword-brief-generator

Store publication remains an explicit manual action. This product is not affiliated with or endorsed by the upstream source unless the Store listing explicitly states otherwise.