Classify Social¶
Classify Social Calls
POST classify/social¶
Classify a list of social posts and return scored categories and keywords.
There is a hard limit of 1,000 posts per call.
Parameters¶
Parameter | Type | Description |
---|---|---|
social (required) | array | A list (no more than 1,000 items) of strings. |
classification_type (optional) | integer | Select the classification method: 1 for rule-based, 2 for model-based, or 0 for a hybrid rule-based + model-based (defaults to 1 ) |
ml_threshold (optional) | float | Specify a confidence threshold for accepting an ML prediction. A lower value increases recall at the expense of precision (defaults to 0.75 ) |
flags (optional) | boolean | Provide Object Flags to help filter out certain content categories including adult, firearms, gambling, etc (defaults to false ) |
entities (optional) | boolean | Perform Named Entity Recognition (NER) on the content submitted (defaults to false ) |
sentiment (optional) | boolean | Perform sentiment analysis on the content submitted (defaults to false ) |
taxonomy_timestamp (optional) | integer | A Unix timestamp instructing the classifier to use categories from the eContext Taxonomy that existed at this point in time. This will allow recently deleted categories to remain and hides newly created categories |
dataset_id (optional) | string | A Custom Taxonomies id to use in lieu of the default eContext Taxonomy |
add_last_node (optional) | bool | Include the last category node, or leave at the parent category |
classify_limit (optional) | integer | Limit the number of categories that may be returned per post |
classify_timeout (optional) | float | The number of seconds to spend on a classification task |
Return¶
The result set includes scored_categories
and scored_keywords
as well as a categories
dictionary. The
scored_keywords
object contains a list of high-value phrases that eContext was able to pull out of the submitted
text as well as associated scores for each. The scored_categories
object contains a list of category_id
and
score
objects where the category_id
corresponds to an item in the categories
dictionary. Higher values
indicate a higher score.
Example Request¶
POST Request¶
curl -X POST -u username:password --data-binary @classify-social-input.json \ --header "Content-type: application/json" \ https://api.econtext.com/v2/classify/social
The contents of classify-social-input.json
:
{
"entities":true,
"flags":true,
"sentiment":true,
"social":[
"HAPPY PI DAY 3.141592653589793238462643383279502884197169399375...",
"Happy birthday, MIT! The Institute was founded April 10, 1861 by William Barton Rogers. #tbt",
"Consciousness is a state of matter",
"Flying car by @MITAeroAstro spinoff @Terrafugia moves from science fiction to reality",
"Amazing Time-Lapse Video Shows Evolution of #Universe Like Never Before",
"MIT alum @JeopardyJulia now trails only @kenjennings for all-time #Jeopardy! wins",
"Happy b-day Nikola #Tesla! Startup @WiTricity is bringing his ideas on wireless power to life",
"Seen at the Student Center this afternoon: Tetris hash browns!",
"Researchers at @eapsMIT say a large earthquake may occur 5 miles from Istanbul",
"MIT's robotic cheetah can now run and jump untethered",
"Spacesuit from @MITAeroAstro shrink-wraps to astronauts' bodies",
"This social post should be flagged for fireworks and gambling references"
]
}
POST Response¶
{
"econtext": {
"classify": {
"results": [
{
"scored_categories": [
{
"category_id": "392e0d5873231ed423359e4ac5b8d27c",
"score": 1
}
],
"scored_keywords": [
{
"keyword": "pi day",
"score": 1
}
],
"flags": [],
"entities": [],
"sentiment": 0.7257
},
{
"scored_categories": [
{
"category_id": "e1a54dc1ecf8e9e2e08505f237fb5968",
"score": 0.5
},
{
"category_id": "351fce59b166d4c9bd4f7e2714a63a44",
"score": 0.5
}
],
"scored_keywords": [
{
"keyword": "birthday",
"score": 0.5
},
{
"keyword": "tbt",
"score": 0.5
}
],
"flags": [],
"entities": [
{
"category_id": "d43dd02c-697b-54be-ac60-a93d6ae39f18",
"type": "ORG"
},
{
"category_id": "99eb4ac4-974f-5805-b729-ef7a2b944c4d",
"type": "ORG"
},
{
"category_id": "d68982ca-a1f0-5c73-a435-6b7f427f0a9c",
"type": "PERSON"
}
],
"sentiment": 0.9129
},
{
"scored_categories": [],
"scored_keywords": [],
"flags": [],
"entities": [
{
"category_id": "723d7837-7b3d-5814-801c-eec10bfa0ef2",
"type": "ORG"
}
],
"sentiment": 0.5637
},
{
"scored_categories": [
{
"category_id": "e77926f4edd0802c8ccae902ca3ab481",
"score": 0.5
},
{
"category_id": "f92c6cc9611ee197c2b747583ae27bb7",
"score": 0.5
}
],
"scored_keywords": [
{
"keyword": "flying car",
"score": 0.5
},
{
"keyword": "science fiction",
"score": 0.5
}
],
"flags": [],
"entities": [
{
"category_id": "5ac57804-0e72-5fe5-a302-8f3b483d4e30",
"type": "ORG"
}
],
"sentiment": 0.5339
},
{
"scored_categories": [
{
"category_id": "c3c123ab122a63e915c59bfb4452f963",
"score": 1
}
],
"scored_keywords": [
{
"keyword": "time-lapse video",
"score": 1
}
],
"flags": [],
"entities": [
{
"category_id": "34458de6-1faf-51a7-8faa-d7b400443fbd",
"type": "ORG"
}
],
"sentiment": 0.8255
},
{
"scored_categories": [
{
"category_id": "167552b27327fc95f4dd5ad057660454",
"score": 1
}
],
"scored_keywords": [
{
"keyword": "@kenjennings",
"score": 1
}
],
"flags": [],
"entities": [
{
"category_id": "d43dd02c-697b-54be-ac60-a93d6ae39f18",
"type": "ORG"
},
{
"category_id": "54b598f0-8b19-5311-8acb-d18bd079fdcc",
"type": "PRODUCT"
}
],
"sentiment": 0.7818
},
{
"scored_categories": [
{
"category_id": "351fce59b166d4c9bd4f7e2714a63a44",
"score": 1
}
],
"scored_keywords": [
{
"keyword": "b-day",
"score": 1
}
],
"flags": [],
"entities": [
{
"category_id": "100190ae-3bd4-5c47-bce2-4b314a4bc784",
"type": "ORG"
},
{
"category_id": "6cf60af7-cc35-5cb0-9096-0b572f746fd1",
"type": "PERSON"
}
],
"sentiment": 0.8256
},
{
"scored_categories": [
{
"category_id": "b675e7ef766cdf32e0cd88dc126d1298",
"score": 0.33333333333333
},
{
"category_id": "6c40a85c0e21602bd49dac13495c442a",
"score": 0.33333333333333
},
{
"category_id": "beb03942afeb6c7819a1ebd803b17246",
"score": 0.33333333333333
}
],
"scored_keywords": [
{
"keyword": "student",
"score": 0.33333333333333
},
{
"keyword": "tetris",
"score": 0.33333333333333
},
{
"keyword": "hash browns",
"score": 0.33333333333333
}
],
"flags": [],
"entities": [
{
"category_id": "3bbb442f-3415-53a4-bac2-7d05718c2029",
"type": "FAC"
},
{
"category_id": "6c40a85c0e21602bd49dac13495c442a",
"type": "GPE"
}
],
"sentiment": 0.6415
},
{
"scored_categories": [
{
"category_id": "416f528d257c527be78186310f94d849",
"score": 1
}
],
"scored_keywords": [
{
"keyword": "large earthquake",
"score": 1
}
],
"flags": [],
"entities": [
{
"category_id": "14aa8718-b2c3-5289-a36c-97ef96951219",
"type": "ORG"
},
{
"category_id": "8c4decd2-a521-5b78-b832-b612a18c693d",
"type": "GPE"
}
],
"sentiment": 0.4232
},
{
"scored_categories": [
{
"category_id": "f49381198e13b2bb011acabb7aff46ea",
"score": 1
}
],
"scored_keywords": [
{
"keyword": "robotic",
"score": 1
}
],
"flags": [],
"entities": [
{
"category_id": "1f3c312f-04bb-5c64-8163-86b93eff1fc5",
"type": "ORG"
}
],
"sentiment": 0.9021
},
{
"scored_categories": [
{
"category_id": "41ed5d3e1d4025ff4c948a4522995797",
"score": 0.33333333333333
},
{
"category_id": "a9a0477ed754171d68bc94058b3f9a40",
"score": 0.33333333333333
},
{
"category_id": "377821e5967fbda300d6bd59cca3aa01",
"score": 0.33333333333333
}
],
"scored_keywords": [
{
"keyword": "spacesuit",
"score": 0.33333333333333
},
{
"keyword": "shrink-wraps",
"score": 0.33333333333333
},
{
"keyword": "astronauts",
"score": 0.33333333333333
}
],
"flags": [],
"entities": [],
"sentiment": 0.5811
},
{
"scored_categories": [
{
"category_id": "cc293f9a2ec42c5438ee90751be03b94",
"score": 0.5
},
{
"category_id": "7705bcc505f80038f272c7de24a8e6a1",
"score": 0.5
}
],
"scored_keywords": [
{
"keyword": "fireworks",
"score": 0.5
},
{
"keyword": "gambling",
"score": 0.5
}
],
"flags": [
{
"flag_id": 32,
"priority": 1,
"listname": [
"banned",
"content"
]
},
{
"flag_id": 32,
"priority": 1,
"listname": [
"banned",
"content"
]
},
{
"flag_id": 16,
"priority": 1,
"listname": [
"banned",
"content"
]
}
],
"entities": [],
"sentiment": 0.159
}
],
"categories": {
"392e0d5873231ed423359e4ac5b8d27c": {
"id": "392e0d5873231ed423359e4ac5b8d27c",
"name": "Pi Day",
"path": [
"Sciences \u0026 Humanities",
"Science",
"Formal Sciences",
"Mathematics",
"Principles of Mathematics",
"Numbers \u0026 Numeration Systems",
"Mathematical Constants",
"Pi",
"Pi Day"
],
"idpath": [
"9c15c34150b7e723fea0eb4b12878947",
"9954bdf75b1d9c9abde66f5fa8d8754f",
"53d4c0d1fbbd7ace2bdabd3264a46780",
"4ce53ea2a04fa3630d9c6f7599836f61",
"0ab4242bf063fa7ffe5000496ca39e03",
"5eece07c994aac582de59a2549fac7aa",
"ed7c6e73c81e81c9793622b95ad63a2f",
"94a5ef1f4eb4fe9dd575adb525961b36",
"392e0d5873231ed423359e4ac5b8d27c"
],
"stats": {
"social_relevance": 5.908e-6,
"social_idf": 11.8204439717
},
"facets": []
},
"351fce59b166d4c9bd4f7e2714a63a44": {
"id": "351fce59b166d4c9bd4f7e2714a63a44",
"name": "Birthdays",
"path": [
"People \u0026 Society",
"Holidays \u0026 Special Events",
"Personal \u0026 General Events",
"Birthdays"
],
"idpath": [
"4bfa345531d3a9bff09432c924bcc729",
"cbbc7e6a1c50cc3c7e4d71a36b472834",
"0d19238741a70ddbb290a4fe4a6d6f48",
"351fce59b166d4c9bd4f7e2714a63a44"
],
"stats": {
"social_relevance": 0.0036452819,
"social_idf": 5.3955573311
},
"facets": [
[
"domain",
"event"
]
]
},
"e1a54dc1ecf8e9e2e08505f237fb5968": {
"id": "e1a54dc1ecf8e9e2e08505f237fb5968",
"name": "Throwback Thursday",
"path": [
"Computers \u0026 Electronics",
"Telecommunications",
"Internet",
"Websites \u0026 Digital Content",
"Memes \u0026 Hashtags",
"Throwback Thursday"
],
"idpath": [
"bdc03d860e5f33c08146faa43487c1bd",
"2712a67ea6c5398779d806a7a5f016eb",
"bbd7a35fae11c6cde461e75bd99e1b1a",
"78971b721e12d951c071b2e3d01c74e8",
"00b261e650d58689f4c50f6728f90d33",
"e1a54dc1ecf8e9e2e08505f237fb5968"
],
"stats": {
"social_relevance": 0.0001028757,
"social_idf": 8.9632244211
},
"facets": []
},
"f92c6cc9611ee197c2b747583ae27bb7": {
"id": "f92c6cc9611ee197c2b747583ae27bb7",
"name": "Flying Cars",
"path": [
"Vehicles",
"Automotive",
"Automotive Vehicles",
"Cars",
"Cars [No Make or Model Specified]",
"Concept Cars",
"Flying Cars"
],
"idpath": [
"164558a2ed9ad8d0a53b550c47f59a8d",
"351eb1e0259f83174a2d0989dd59b362",
"0e2aef22ab0d79d841d91eb4f88182de",
"1e8320e16458428adfa0a0c437960883",
"3ed56d5fe16ef7b9015e18beb22a3af5",
"bd8525cf683b6bc0079481e3b342940e",
"f92c6cc9611ee197c2b747583ae27bb7"
],
"stats": {
"social_relevance": 7.3207e-6,
"social_idf": 11.6060341003
},
"facets": []
},
"e77926f4edd0802c8ccae902ca3ab481": {
"id": "e77926f4edd0802c8ccae902ca3ab481",
"name": "Science Fiction",
"path": [
"Arts \u0026 Entertainment",
"General Arts \u0026 Entertainment",
"Arts \u0026 Entertainment Reference",
"Arts \u0026 Entertainment Genres",
"Science Fiction"
],
"idpath": [
"90a7a21c5fe42569fb5bb0d28ce9f77a",
"510ab43297466c29e7c115a5deb9e829",
"274625376346f0c0f766cd7214aee558",
"6a3d1570b55a8c6f8e13cf208bad8c48",
"e77926f4edd0802c8ccae902ca3ab481"
],
"stats": {
"social_relevance": 6.10062e-5,
"social_idf": 9.4857705641
},
"facets": []
},
"c3c123ab122a63e915c59bfb4452f963": {
"id": "c3c123ab122a63e915c59bfb4452f963",
"name": "Time Lapse Photography",
"path": [
"Arts \u0026 Entertainment",
"Art \u0026 Architecture",
"Photographic \u0026 Digital Arts",
"Photography",
"Photography Reference",
"Photography Styles",
"Time Lapse Photography"
],
"idpath": [
"90a7a21c5fe42569fb5bb0d28ce9f77a",
"9c5fe10a2ef8ec077a3e9f6f9716832c",
"e2d5a95ec2e5449aa3ca32200dc1ba11",
"e2a24e73ddf0f86f4b24bb0b63de8c7a",
"f27736734d08638cfeff796c613d9f94",
"3e69664a4bf73930e84ab9c04d5aa29b",
"c3c123ab122a63e915c59bfb4452f963"
],
"stats": {
"social_relevance": 1.7339e-6,
"social_idf": 13.0463956827
},
"facets": []
},
"167552b27327fc95f4dd5ad057660454": {
"id": "167552b27327fc95f4dd5ad057660454",
"name": "Ken Jennings",
"path": [
"Books \u0026 Literature",
"Writers",
"Authors",
"Ken Jennings"
],
"idpath": [
"abbae30350b924c4dffcbffc3052b450",
"42ed27bd6214641b86d538bb6e68a19a",
"f1e46f3f9726db4cd8fae40fe06b48bf",
"167552b27327fc95f4dd5ad057660454"
],
"stats": {
"social_relevance": 1.7981e-6,
"social_idf": 13.0100280386
},
"facets": []
},
"beb03942afeb6c7819a1ebd803b17246": {
"id": "beb03942afeb6c7819a1ebd803b17246",
"name": "Students",
"path": [
"Jobs \u0026 Education",
"Education",
"Education [No Level Specified]",
"Education Resources \u0026 Information",
"Educational Resources \u0026 Information [No Subject Specified]",
"Students"
],
"idpath": [
"65ace7f404e084a6a2d7f326aa5d8643",
"7cb98cd3218f67a46f65485e02dcd50f",
"e77975649d2ad1259aeea1b242cc0579",
"2d558f872db06bb225d62b6cf7616563",
"512669d0b764d09998518c04946752da",
"beb03942afeb6c7819a1ebd803b17246"
],
"stats": {
"social_relevance": 0.0011491644,
"social_idf": 6.5499559255
},
"facets": []
},
"6c40a85c0e21602bd49dac13495c442a": {
"id": "6c40a85c0e21602bd49dac13495c442a",
"name": "Tetris",
"path": [
"Games \u0026 Toys",
"Video Games",
"Video Game Products",
"Video Game Titles",
"Puzzle Video Games",
"Tetris Video Game Series",
"Tetris"
],
"idpath": [
"798f51fd6b8d172fa4fd718313c8c4c6",
"761a66aa4f58df6fdc5151837e392ffa",
"e85b2a2795db3616a2e4efe77e9763d3",
"d88ad5e8fd267e2df8bdc6f257dd8051",
"b00536cd955c6954df027e65017046f5",
"5a6e03a1f3b3a7890f2941156e8faf89",
"6c40a85c0e21602bd49dac13495c442a"
],
"stats": {
"social_relevance": 1.51552e-5,
"social_idf": 10.8784007437
},
"facets": [
[
"domain",
"product"
],
[
"brand",
"tetris"
]
]
},
"b675e7ef766cdf32e0cd88dc126d1298": {
"id": "b675e7ef766cdf32e0cd88dc126d1298",
"name": "Hash Browns",
"path": [
"Food \u0026 Drink",
"Food",
"Produce",
"Vegetables",
"Potatoes",
"Potatoes [No Brand Specified]",
"Potato Dishes",
"Hash Browns"
],
"idpath": [
"18a737475478cc2140c5418862bf811a",
"42c09908ce0d200e3b712f804de7b283",
"fb3bc8da4d080e30af482bd523498992",
"e30d80dee7d477dfafe3f344670f46ba",
"87926bc9eabd9abe320173a55d48e7f3",
"e61d6aa6636b9191a31e48545cbd4eec",
"af9534726aae10528debab1c4ed8945e",
"b675e7ef766cdf32e0cd88dc126d1298"
],
"stats": {
"social_relevance": 1.15591e-5,
"social_idf": 11.1492756978
},
"facets": []
},
"416f528d257c527be78186310f94d849": {
"id": "416f528d257c527be78186310f94d849",
"name": "Largest Earthquakes",
"path": [
"Sciences \u0026 Humanities",
"Science",
"Natural Sciences",
"Earth Sciences",
"Branches of Earth Science",
"Geology",
"Geological Events",
"Natural Disasters",
"Earthquakes",
"Largest Earthquakes"
],
"idpath": [
"9c15c34150b7e723fea0eb4b12878947",
"9954bdf75b1d9c9abde66f5fa8d8754f",
"36c3f922da8fc76f982280ca44c8e4b8",
"3f98be34278d9e5a70bedafb5b31e8b2",
"a92ee8be0d06baa40a30a7066666fd84",
"c92f3d571292cadaece36a486dc5503a",
"6b362f1c0b4c37b1d31559b306160853",
"a660fb9474473991080ee711cdf56df9",
"75226c51631fd2d9e1a1f30d00db44a8",
"416f528d257c527be78186310f94d849"
],
"stats": {
"social_relevance": 3.6604e-6,
"social_idf": 12.2991812809
},
"facets": []
},
"f49381198e13b2bb011acabb7aff46ea": {
"id": "f49381198e13b2bb011acabb7aff46ea",
"name": "Robotics",
"path": [
"Sciences \u0026 Humanities",
"Science",
"Applied Sciences",
"Branches of Applied Science",
"Engineering \u0026 Technology Sciences",
"Robotics"
],
"idpath": [
"9c15c34150b7e723fea0eb4b12878947",
"9954bdf75b1d9c9abde66f5fa8d8754f",
"a2c3e64fb366e35a012b6e69dac465cd",
"8f82615dd462926368531bf0b109589f",
"d1702de50ae24507ea3d26a7baf80773",
"f49381198e13b2bb011acabb7aff46ea"
],
"stats": {
"social_relevance": 3.2237e-5,
"social_idf": 10.123632429
},
"facets": []
},
"377821e5967fbda300d6bd59cca3aa01": {
"id": "377821e5967fbda300d6bd59cca3aa01",
"name": "Space Suits",
"path": [
"Sciences \u0026 Humanities",
"Science",
"Applied Sciences",
"Branches of Applied Science",
"Engineering \u0026 Technology Sciences",
"Space Technologies",
"Space Travel",
"Space Travel [No Agency Specified]",
"Space Suits"
],
"idpath": [
"9c15c34150b7e723fea0eb4b12878947",
"9954bdf75b1d9c9abde66f5fa8d8754f",
"a2c3e64fb366e35a012b6e69dac465cd",
"8f82615dd462926368531bf0b109589f",
"d1702de50ae24507ea3d26a7baf80773",
"904fdc839f95149a2b9dfac6fb7f2069",
"d65f3cfe264d132de0b9b811cb905c37",
"c907f49501034ae4f62e0fb9a3b006a5",
"377821e5967fbda300d6bd59cca3aa01"
],
"stats": {
"social_relevance": 3.6604e-6,
"social_idf": 12.2991812809
},
"facets": []
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