How to get Dcard Topics & Trends by webhook

Monitor public Dcard topics without an account. dcard.tw is one page of it. A run reads that public list and saves one row per result.

Set up the Apify actor

Apify is where this run is collected. An actor is the program that collects the rows. A task is that program saved with your settings, so the next section can ask for the latest rows. You need a free Apify account.

01
Open Dcard Topics & Trends and click Try for free. Create an Apify account if you do not have one. The Free plan does not ask for a card.

You are on the input form. Keep the sample for this first run.

{
    "topicUrls": [
        "https://www.dcard.tw/topics/%E7%9C%81%E9%8C%A2"
    ],
    "maxItems": 1,
    "samplePostsPerTopic": 0,
    "includeLatest": false,
    "includeTrending": true
}

03
Leave the proxy setting as it is. Click Start and wait until the run says Succeeded.
04
Open Storage, then Dataset. You should see topicName, topicUrl, followerCount, postCount.
05
When you want the real list, raise maxItems. The sample cap is only there so the first run stays small.
06
Go back to the input and choose Save as a new task. Name it after this list.
07
Open the task. Copy the task ID from the address bar. Excel, Sheets, Power BI, and the other guides ask for this ID.
08
On the task, open Schedules and add a weekly run if you want fresh rows. Each run pays the start charge and the charge for the rows. The amounts are in the price list on this page.
09
Open Settings, then API & Integrations, and copy an API token. Excel, Sheets, and the other guides put this token in a download link. Anyone with that link can download the rows, so treat it like a password.

How to set up a webhook

Use the task ID and the API token from Set up the Apify actor, above.

01
In Apify, open Dcard Topics & Trends and go to Integrations.
02
Add a webhook for Actor run succeeded. Point it at the URL that should receive the run.
03
The payload includes the dataset id. Read the rows from that dataset, or from the task URL in the sections above.
04
The weekly schedule from Set up the Apify actor, above, is what makes this fire every week.

Schema

Examples come from the actor sample, not a live result.

Name	Description	Example
`topicName`	Public topic label	`AI`
`topicUrl`	Canonical public topic URL	`https://www.dcard.tw/topics/AI`
`followerCount`	Public follower count, when Dcard exposes it	`12345`
`postCount`	Public topic post count, when exposed	`987`
`latestPosts`	Sampled latest posts with URL, title, date, and public engagement	`[{"id":260002,"url":"https://www.dcard.tw/f/3c/p/260002","title":"AI 工具實測","forumAlias":"3c","createdAt":"2026-10-02T00:00:00.000Z","likeCount":12,"commentCount":4,"shareCount":nul`
`trendingPosts`	Sampled popular/trending posts with the same fields	`[]`
`observedPostCount`	Unique posts actually present in the two samples	`1`
`observedEngagementCount`	Sum of exposed likes, comments, and shares across observed posts	`16`
`observedAverageEngagement`	Average over posts whose engagement was exposed	`16`
`observedMaxEngagement`	Highest exposed sampled-post engagement	`16`

topicNamePublic topic labelAI
topicUrlCanonical public topic URLhttps://www.dcard.tw/topics/AI
followerCountPublic follower count, when Dcard exposes it12345
postCountPublic topic post count, when exposed987
latestPostsSampled latest posts with URL, title, date, and public engagement[{"id":260002,"url":"https://www.dcard.tw/f/3c/p/260002","title":"AI 工具實測","forumAlias":"3c","createdAt":"2026-10-02T00:00:00.000Z","likeCount":12,"commentCount":4,"shareCount":nul
trendingPostsSampled popular/trending posts with the same fields[]
observedPostCountUnique posts actually present in the two samples1
observedEngagementCountSum of exposed likes, comments, and shares across observed posts16
observedAverageEngagementAverage over posts whose engagement was exposed16
observedMaxEngagementHighest exposed sampled-post engagement16