A small tool to view real-world ActivityPub objects as JSON! Enter a URL
or username from Mastodon or a similar service below, and we'll send a
request with
the right
Accept
header
to the server to view the underlying object.
{
"@context": [
"https://www.w3.org/ns/activitystreams",
{
"ostatus": "http://ostatus.org#",
"atomUri": "ostatus:atomUri",
"inReplyToAtomUri": "ostatus:inReplyToAtomUri",
"conversation": "ostatus:conversation",
"sensitive": "as:sensitive",
"toot": "http://joinmastodon.org/ns#",
"votersCount": "toot:votersCount"
}
],
"id": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097/activity",
"type": "Create",
"actor": "https://mathstodon.xyz/users/dlzv",
"published": "2022-04-29T18:18:09Z",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://mathstodon.xyz/users/dlzv/followers",
"https://mathstodon.xyz/users/jt"
],
"object": {
"id": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097",
"type": "Note",
"summary": null,
"inReplyTo": "https://mathstodon.xyz/users/jt/statuses/108216711136010455",
"published": "2022-04-29T18:18:09Z",
"url": "https://mathstodon.xyz/@dlzv/108216732157931097",
"attributedTo": "https://mathstodon.xyz/users/dlzv",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://mathstodon.xyz/users/dlzv/followers",
"https://mathstodon.xyz/users/jt"
],
"sensitive": false,
"atomUri": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097",
"inReplyToAtomUri": "https://mathstodon.xyz/users/jt/statuses/108216711136010455",
"conversation": "tag:mathstodon.xyz,2022-04-29:objectId=24829807:objectType=Conversation",
"content": "<p><span class=\"h-card\" translate=\"no\"><a href=\"https://mathstodon.xyz/@jt\" class=\"u-url mention\">@<span>jt</span></a></span> I'm not very familiar with Bayesian models for NLP, do you have some pointers? For what it's worth, there are pretrained models that can be used with very few data now if you're interested. Of course understanding them deeply is another issue...</p>",
"contentMap": {
"en": "<p><span class=\"h-card\" translate=\"no\"><a href=\"https://mathstodon.xyz/@jt\" class=\"u-url mention\">@<span>jt</span></a></span> I'm not very familiar with Bayesian models for NLP, do you have some pointers? For what it's worth, there are pretrained models that can be used with very few data now if you're interested. Of course understanding them deeply is another issue...</p>"
},
"attachment": [],
"tag": [
{
"type": "Mention",
"href": "https://mathstodon.xyz/users/jt",
"name": "@jt"
}
],
"replies": {
"id": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097/replies",
"type": "Collection",
"first": {
"type": "CollectionPage",
"next": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097/replies?only_other_accounts=true&page=true",
"partOf": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097/replies",
"items": []
}
},
"likes": {
"id": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097/likes",
"type": "Collection",
"totalItems": 0
},
"shares": {
"id": "https://mathstodon.xyz/users/dlzv/statuses/108216732157931097/shares",
"type": "Collection",
"totalItems": 0
}
}
}