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",
"Hashtag": "as:Hashtag"
}
],
"id": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919",
"type": "Note",
"summary": null,
"inReplyTo": "https://sigmoid.social/users/predict_addict/statuses/114048124904310043",
"published": "2025-02-22T14:58:06Z",
"url": "https://sigmoid.social/@predict_addict/114048125261360919",
"attributedTo": "https://sigmoid.social/users/predict_addict",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://sigmoid.social/users/predict_addict/followers"
],
"sensitive": false,
"atomUri": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919",
"inReplyToAtomUri": "https://sigmoid.social/users/predict_addict/statuses/114048124904310043",
"conversation": "tag:sigmoid.social,2025-02-22:objectId=51794276:objectType=Conversation",
"content": "<p>Have you seen traditional methods outperform deep learning in your work? Let’s discuss! ⬇️ </p><p><a href=\"https://sigmoid.social/tags/TimeSeries\" class=\"mention hashtag\" rel=\"tag\">#<span>TimeSeries</span></a> <a href=\"https://sigmoid.social/tags/MachineLearning\" class=\"mention hashtag\" rel=\"tag\">#<span>MachineLearning</span></a> <a href=\"https://sigmoid.social/tags/Forecasting\" class=\"mention hashtag\" rel=\"tag\">#<span>Forecasting</span></a> <a href=\"https://sigmoid.social/tags/AI\" class=\"mention hashtag\" rel=\"tag\">#<span>AI</span></a> <a href=\"https://sigmoid.social/tags/DataScience\" class=\"mention hashtag\" rel=\"tag\">#<span>DataScience</span></a> <a href=\"https://sigmoid.social/tags/DeepLearning\" class=\"mention hashtag\" rel=\"tag\">#<span>DeepLearning</span></a> <a href=\"https://sigmoid.social/tags/Statistics\" class=\"mention hashtag\" rel=\"tag\">#<span>Statistics</span></a> <a href=\"https://sigmoid.social/tags/AIResearch\" class=\"mention hashtag\" rel=\"tag\">#<span>AIResearch</span></a> <a href=\"https://sigmoid.social/tags/GoogleVertexAI\" class=\"mention hashtag\" rel=\"tag\">#<span>GoogleVertexAI</span></a> <a href=\"https://sigmoid.social/tags/TimeSeriesForecasting\" class=\"mention hashtag\" rel=\"tag\">#<span>TimeSeriesForecasting</span></a></p>",
"contentMap": {
"en": "<p>Have you seen traditional methods outperform deep learning in your work? Let’s discuss! ⬇️ </p><p><a href=\"https://sigmoid.social/tags/TimeSeries\" class=\"mention hashtag\" rel=\"tag\">#<span>TimeSeries</span></a> <a href=\"https://sigmoid.social/tags/MachineLearning\" class=\"mention hashtag\" rel=\"tag\">#<span>MachineLearning</span></a> <a href=\"https://sigmoid.social/tags/Forecasting\" class=\"mention hashtag\" rel=\"tag\">#<span>Forecasting</span></a> <a href=\"https://sigmoid.social/tags/AI\" class=\"mention hashtag\" rel=\"tag\">#<span>AI</span></a> <a href=\"https://sigmoid.social/tags/DataScience\" class=\"mention hashtag\" rel=\"tag\">#<span>DataScience</span></a> <a href=\"https://sigmoid.social/tags/DeepLearning\" class=\"mention hashtag\" rel=\"tag\">#<span>DeepLearning</span></a> <a href=\"https://sigmoid.social/tags/Statistics\" class=\"mention hashtag\" rel=\"tag\">#<span>Statistics</span></a> <a href=\"https://sigmoid.social/tags/AIResearch\" class=\"mention hashtag\" rel=\"tag\">#<span>AIResearch</span></a> <a href=\"https://sigmoid.social/tags/GoogleVertexAI\" class=\"mention hashtag\" rel=\"tag\">#<span>GoogleVertexAI</span></a> <a href=\"https://sigmoid.social/tags/TimeSeriesForecasting\" class=\"mention hashtag\" rel=\"tag\">#<span>TimeSeriesForecasting</span></a></p>"
},
"attachment": [],
"tag": [
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/TimeSeries",
"name": "#TimeSeries"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/machinelearning",
"name": "#machinelearning"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/forecasting",
"name": "#forecasting"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/ai",
"name": "#ai"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/DataScience",
"name": "#DataScience"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/deeplearning",
"name": "#deeplearning"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/statistics",
"name": "#statistics"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/AiResearch",
"name": "#AiResearch"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/googlevertexai",
"name": "#googlevertexai"
},
{
"type": "Hashtag",
"href": "https://sigmoid.social/tags/timeseriesforecasting",
"name": "#timeseriesforecasting"
}
],
"replies": {
"id": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919/replies",
"type": "Collection",
"first": {
"type": "CollectionPage",
"next": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919/replies?min_id=114048125607620382&page=true",
"partOf": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919/replies",
"items": [
"https://sigmoid.social/users/predict_addict/statuses/114048125607620382"
]
}
},
"likes": {
"id": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919/likes",
"type": "Collection",
"totalItems": 0
},
"shares": {
"id": "https://sigmoid.social/users/predict_addict/statuses/114048125261360919/shares",
"type": "Collection",
"totalItems": 3
}
}