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://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474",
"type": "Note",
"summary": null,
"inReplyTo": null,
"published": "2024-11-05T08:17:04Z",
"url": "https://mastodon.social/@StatisticsGlobe/113429356512387474",
"attributedTo": "https://mastodon.social/users/StatisticsGlobe",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://mastodon.social/users/StatisticsGlobe/followers"
],
"sensitive": false,
"atomUri": "https://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474",
"inReplyToAtomUri": null,
"conversation": "tag:mastodon.social,2024-11-05:objectId=839993162:objectType=Conversation",
"content": "<p>In Bayesian inference, a credible interval is a range of values within which a parameter lies with a certain probability, given the observed data and prior beliefs. The image of this post (based on this Wikipedia image: <a href=\"https://en.wikipedia.org/wiki/Credible_interval#/media/File:Highest_posterior_density_interval.svg\" target=\"_blank\" rel=\"nofollow noopener\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"ellipsis\">en.wikipedia.org/wiki/Credible</span><span class=\"invisible\">_interval#/media/File:Highest_posterior_density_interval.svg</span></a>) represents a 90% highest-density credible interval of a posterior probability distribution.</p><p>More details: <a href=\"http://eepurl.com/gH6myT\" target=\"_blank\" rel=\"nofollow noopener\" translate=\"no\"><span class=\"invisible\">http://</span><span class=\"\">eepurl.com/gH6myT</span><span class=\"invisible\"></span></a></p><p><a href=\"https://mastodon.social/tags/statistical\" class=\"mention hashtag\" rel=\"tag\">#<span>statistical</span></a> <a href=\"https://mastodon.social/tags/datasciencecourse\" class=\"mention hashtag\" rel=\"tag\">#<span>datasciencecourse</span></a> <a href=\"https://mastodon.social/tags/datascience\" class=\"mention hashtag\" rel=\"tag\">#<span>datascience</span></a> <a href=\"https://mastodon.social/tags/rprogramming\" class=\"mention hashtag\" rel=\"tag\">#<span>rprogramming</span></a> <a href=\"https://mastodon.social/tags/datastructure\" class=\"mention hashtag\" rel=\"tag\">#<span>datastructure</span></a></p>",
"contentMap": {
"en": "<p>In Bayesian inference, a credible interval is a range of values within which a parameter lies with a certain probability, given the observed data and prior beliefs. The image of this post (based on this Wikipedia image: <a href=\"https://en.wikipedia.org/wiki/Credible_interval#/media/File:Highest_posterior_density_interval.svg\" target=\"_blank\" rel=\"nofollow noopener\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"ellipsis\">en.wikipedia.org/wiki/Credible</span><span class=\"invisible\">_interval#/media/File:Highest_posterior_density_interval.svg</span></a>) represents a 90% highest-density credible interval of a posterior probability distribution.</p><p>More details: <a href=\"http://eepurl.com/gH6myT\" target=\"_blank\" rel=\"nofollow noopener\" translate=\"no\"><span class=\"invisible\">http://</span><span class=\"\">eepurl.com/gH6myT</span><span class=\"invisible\"></span></a></p><p><a href=\"https://mastodon.social/tags/statistical\" class=\"mention hashtag\" rel=\"tag\">#<span>statistical</span></a> <a href=\"https://mastodon.social/tags/datasciencecourse\" class=\"mention hashtag\" rel=\"tag\">#<span>datasciencecourse</span></a> <a href=\"https://mastodon.social/tags/datascience\" class=\"mention hashtag\" rel=\"tag\">#<span>datascience</span></a> <a href=\"https://mastodon.social/tags/rprogramming\" class=\"mention hashtag\" rel=\"tag\">#<span>rprogramming</span></a> <a href=\"https://mastodon.social/tags/datastructure\" class=\"mention hashtag\" rel=\"tag\">#<span>datastructure</span></a></p>"
},
"attachment": [
{
"type": "Document",
"mediaType": "image/png",
"url": "https://files.mastodon.social/media_attachments/files/113/429/356/312/130/742/original/0ab76c7d77317d85.png",
"name": null,
"blurhash": "UQNTeM4Y.7.64hxsIWV]0T%LV_IW4wR*%Kt6",
"width": 1024,
"height": 584
}
],
"tag": [
{
"type": "Hashtag",
"href": "https://mastodon.social/tags/statistical",
"name": "#statistical"
},
{
"type": "Hashtag",
"href": "https://mastodon.social/tags/datasciencecourse",
"name": "#datasciencecourse"
},
{
"type": "Hashtag",
"href": "https://mastodon.social/tags/datascience",
"name": "#datascience"
},
{
"type": "Hashtag",
"href": "https://mastodon.social/tags/rprogramming",
"name": "#rprogramming"
},
{
"type": "Hashtag",
"href": "https://mastodon.social/tags/datastructure",
"name": "#datastructure"
}
],
"replies": {
"id": "https://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474/replies",
"type": "Collection",
"first": {
"type": "CollectionPage",
"next": "https://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474/replies?only_other_accounts=true&page=true",
"partOf": "https://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474/replies",
"items": []
}
},
"likes": {
"id": "https://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474/likes",
"type": "Collection",
"totalItems": 0
},
"shares": {
"id": "https://mastodon.social/users/StatisticsGlobe/statuses/113429356512387474/shares",
"type": "Collection",
"totalItems": 0
}
}