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",
"blurhash": "toot:blurhash",
"focalPoint": {
"@container": "@list",
"@id": "toot:focalPoint"
},
"Hashtag": "as:Hashtag"
}
],
"id": "https://sciences.social/users/csmarcum/statuses/114444358152920536",
"type": "Note",
"summary": null,
"inReplyTo": null,
"published": "2025-05-03T14:25:20Z",
"url": "https://sciences.social/@csmarcum/114444358152920536",
"attributedTo": "https://sciences.social/users/csmarcum",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://sciences.social/users/csmarcum/followers"
],
"sensitive": false,
"atomUri": "https://sciences.social/users/csmarcum/statuses/114444358152920536",
"inReplyToAtomUri": null,
"conversation": "tag:sciences.social,2025-05-03:objectId=71980439:objectType=Conversation",
"content": "<p>In 2015, I used spectral analysis (now a standard component of ML algorithms underlying AI) on a sample of rasterized central components of <a href=\"https://sciences.social/tags/BobRoss\" class=\"mention hashtag\" rel=\"tag\">#<span>BobRoss</span></a> paintings. I created the first ever rendering of a pixel-by-pixel "average" bob ross painting. Today, ChatGPT can render an interpretation of "create an average bob ross painting" - fascinatingly, the quantitative results from my preprint map very well to the AI's qualitative interpretation. Read <a href=\"https://sciences.social/tags/preprint\" class=\"mention hashtag\" rel=\"tag\">#<span>preprint</span></a> here: <a href=\"https://doi.org/10.31235/osf.io/pkqd5\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"\">doi.org/10.31235/osf.io/pkqd5</span><span class=\"invisible\"></span></a></p>",
"contentMap": {
"en": "<p>In 2015, I used spectral analysis (now a standard component of ML algorithms underlying AI) on a sample of rasterized central components of <a href=\"https://sciences.social/tags/BobRoss\" class=\"mention hashtag\" rel=\"tag\">#<span>BobRoss</span></a> paintings. I created the first ever rendering of a pixel-by-pixel "average" bob ross painting. Today, ChatGPT can render an interpretation of "create an average bob ross painting" - fascinatingly, the quantitative results from my preprint map very well to the AI's qualitative interpretation. Read <a href=\"https://sciences.social/tags/preprint\" class=\"mention hashtag\" rel=\"tag\">#<span>preprint</span></a> here: <a href=\"https://doi.org/10.31235/osf.io/pkqd5\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"\">doi.org/10.31235/osf.io/pkqd5</span><span class=\"invisible\"></span></a></p>"
},
"attachment": [
{
"type": "Document",
"mediaType": "image/png",
"url": "https://cdn.masto.host/sciencessocial/media_attachments/files/114/444/310/169/048/680/original/e482202ecabe8813.png",
"name": "ChatGPT's rendering of the prompt \"create an average bob ross painting\"",
"blurhash": "UWD0uxo}IUnh_NsmWAkW%gWCozkCSiR*t7WB",
"focalPoint": [
0,
0
],
"width": 1024,
"height": 1536
},
{
"type": "Document",
"mediaType": "image/png",
"url": "https://cdn.masto.host/sciencessocial/media_attachments/files/114/444/328/565/703/718/original/e552c22e26d1c007.png",
"name": "\"average\" colorspace from a sample of 30 bob ross painting raster images",
"blurhash": "UHHoH_j?t7R*s;t7WCa#?wofoeof9FayoIoJ",
"focalPoint": [
0,
0
],
"width": 481,
"height": 495
}
],
"tag": [
{
"type": "Hashtag",
"href": "https://sciences.social/tags/bobross",
"name": "#bobross"
},
{
"type": "Hashtag",
"href": "https://sciences.social/tags/preprint",
"name": "#preprint"
}
],
"replies": {
"id": "https://sciences.social/users/csmarcum/statuses/114444358152920536/replies",
"type": "Collection",
"first": {
"type": "CollectionPage",
"next": "https://sciences.social/users/csmarcum/statuses/114444358152920536/replies?only_other_accounts=true&page=true",
"partOf": "https://sciences.social/users/csmarcum/statuses/114444358152920536/replies",
"items": []
}
},
"likes": {
"id": "https://sciences.social/users/csmarcum/statuses/114444358152920536/likes",
"type": "Collection",
"totalItems": 0
},
"shares": {
"id": "https://sciences.social/users/csmarcum/statuses/114444358152920536/shares",
"type": "Collection",
"totalItems": 0
}
}