Mugen AI Mugen AI Social API

API v1

Programmatic access to social analytics datasets

ソーシャル分析データセットへのAPIアクセス

Query buzz-db and social-db using filter-based payloads. This API is optimized for fast analytical reads and predictable schema-driven responses.

Authentication

api-key: YOUR_API_KEY

Base URL

https://data-api.mugen-ai-social.jp

Flexible filters

Compose SQL-like conditions in JSON with operators like =, contains, and range comparisons.

BigQuery-backed

Designed for analytics workloads with clean projection fields, ordering, and limits.

Schema transparency

Available fields are listed live below for both datasets to speed up query authoring.

Quick start

1

Prepare credentials

Get your API key and keep it private. Every request must include it in the api-key header.

2

Build filters

Define conditions, select_fields, and an explicit date range for better performance.

3

Execute request

Send a POST call to one of the dataset endpoints and iterate quickly with Swagger or ReDoc.

Detailed how to use

Request shape

  • conditions: array of filter clauses.
  • select_fields: optional projection list.
  • order_by + order_dir: optional sorting.
  • limit (1-10000), offset (0-100000).

Operator guide

  • contains performs partial string match.
  • in expects an array value.
  • Use ISO-like dates for date/timestamp fields.
  • Always include a date boundary for cost control.

Output and sorting options

Field What it does Example
select_fields Choose which columns to return. If omitted, default output fields are used. ["date", "user_name", "likes"]
order_by Pick one field for sorting (for example date or likes). "date"
order_dir Sorting direction: "asc" = old/small to new/large, "desc" = reverse. "desc"
limit How many rows to return. Good start: 20-100 for testing. 100
offset Skip rows for pagination. Use 0 for first page, then 100, 200, ... 0

Condition operations (simple guide)

Use this when you are not from an IT background. Pick the operator by what you want to compare.

op Meaning Example
= Exactly equal {"field":"user_name","op":"=","value":"alice"}
!= Not equal {"field":"tweet_type","op":"!=","value":"reply"}
> / >= Greater than / greater or equal {"field":"likes","op":">=","value":100}
< / <= Less than / less or equal {"field":"engagement","op":"<","value":5}
contains Text includes keyword {"field":"text","op":"contains","value":"campaign"}
in Match any value in a list {"field":"media_type","op":"in","value":["image","video"]}

Recommended for beginners: start with date + one simple condition (for example likes >= 100) and test with limit: 20.

POST /v1/buzz-db or /v1/social-db
Headers:
  api-key: YOUR_API_KEY
Body:
{
  "conditions": [{"field": "date", "op": ">=", "value": "2026-03-01"}],
  "select_fields": ["date", "user_name", "text"],
  "order_by": "date",
  "order_dir": "desc",
  "limit": 100,
  "offset": 0
}

Client example call

Choose a language, review the example, then copy it. Default is Python.

import requests

BASE_URL = "https://data-api.mugen-ai-social.jp"
API_KEY = "YOUR_API_KEY"

payload = {
  "conditions": [
    {"field": "date", "op": ">=", "value": "2026-03-01"},
    {"field": "hashtags", "op": "contains", "value": "ai"}
  ],
  "select_fields": ["date", "user_name", "text", "likes"],
  "order_by": "date",
  "order_dir": "desc",
  "limit": 100,
  "offset": 0
}

response = requests.post(
  f"{BASE_URL}/v1/buzz-db",
  headers={"api-key": API_KEY, "Content-Type": "application/json"},
  json=payload,
  timeout=30
)
response.raise_for_status()

print(response.json())

buzz-db fields

86 fields

Column descriptions

Each field includes a quick meaning reference for faster query design.

a01_student

Audience segment score/flag for 'student'.

a02_office_worker

Audience segment score/flag for 'office worker'.

a03_business_owner

Audience segment score/flag for 'business owner'.

a04_housewife_mom

Audience segment score/flag for 'housewife mom'.

a05_househusband_dad

Audience segment score/flag for 'househusband dad'.

b01_creators

Behavior segment score/flag for 'creators'.

b02_parents

Behavior segment score/flag for 'parents'.

b03_news_interest

Behavior segment score/flag for 'news interest'.

b04_marketing_interest

Behavior segment score/flag for 'marketing interest'.

beauty_health

Beauty Health value from source dataset.

bio

Author profile biography text.

bookmarks

Bookmark count.

buzz_element

Detected buzz-driving element tags.

c01_politics

Interest segment score/flag for 'politics'.

c02_economy_finance_investment

Interest segment score/flag for 'economy finance investment'.

c03_research_science

Interest segment score/flag for 'research science'.

c04_it_technology

Interest segment score/flag for 'it technology'.

c05_gadget

Interest segment score/flag for 'gadget'.

c06_outdoor

Interest segment score/flag for 'outdoor'.

c07_travel_solo_travel

Interest segment score/flag for 'travel solo travel'.

c08_sports_viewing

Interest segment score/flag for 'sports viewing'.

c09_music

Interest segment score/flag for 'music'.

c10_movies_dramas

Interest segment score/flag for 'movies dramas'.

c11_design_art

Interest segment score/flag for 'design art'.

c12_history_art_literature

Interest segment score/flag for 'history art literature'.

c13_anime_manga

Interest segment score/flag for 'anime manga'.

c14_games

Interest segment score/flag for 'games'.

c15_idol

Interest segment score/flag for 'idol'.

c16_beauty_fashion

Interest segment score/flag for 'beauty fashion'.

c17_fitness

Interest segment score/flag for 'fitness'.

c18_cooking_gourmet

Interest segment score/flag for 'cooking gourmet'.

c19_alcohol_drinks

Interest segment score/flag for 'alcohol drinks'.

c20_medicine_care

Interest segment score/flag for 'medicine care'.

c21_animals_pets

Interest segment score/flag for 'animals pets'.

c22_lottery_promotion

Interest segment score/flag for 'lottery promotion'.

c23_auto_bike

Interest segment score/flag for 'auto bike'.

c24_gambling

Interest segment score/flag for 'gambling'.

created_at

Source creation timestamp.

d01_generation_z

Demographic segment score/flag for 'generation z'.

d02_generation_y

Demographic segment score/flag for 'generation y'.

d03_generation_x

Demographic segment score/flag for 'generation x'.

d11_teenagers

Demographic segment score/flag for 'teenagers'.

d12_20s

Demographic segment score/flag for '20s'.

d13_30s

Demographic segment score/flag for '30s'.

d14_40s

Demographic segment score/flag for '40s'.

d15_50s

Demographic segment score/flag for '50s'.

d21_female

Demographic segment score/flag for 'female'.

date

Logical partition date for analytics filtering.

diet_restriction

Diet Restriction value from source dataset.

engagement

Computed engagement score or rate.

followers

Follower count for the author.

friends

Following count for the author.

guilty_food

Guilty Food value from source dataset.

gym_exercise_training

Gym Exercise Training value from source dataset.

hashtags

Hashtag list extracted from the post.

id

Internal row identifier.

id_numeric

Numeric identifier for sorting and joins.

insta_recipes_sweets

Insta Recipes Sweets value from source dataset.

is_original

Whether the post is original content.

is_verified

Whether the author account is verified.

likes

Like count.

location

Author-declared location text.

media_links

Referenced media URLs.

media_type

Primary media type attached to the post.

meta_text_length

Length of post text in characters.

original_tweet

Original source post identifier/body reference.

pfp_url

Profile image URL.

qt

Quote post count.

qt_body

Quoted post body text.

qt_count

Number of quote relationships.

qt_kw_list

Keyword list extracted from quoted context.

qt_summary

Summary text of quoted context.

retweets

Retweet or repost count.

str_date

Date represented as raw source string.

text

Post content text.

threads

Thread-related count or marker.

tribe_count

Number of classified tribes for the post/user.

tweet_caption

Normalized or extracted caption text.

tweet_id

Platform-native post identifier.

tweet_type

Post type classification label.

updated_at

Source update timestamp.

url

Source post URL.

user_name

Author username at posting time.

user_tribes

Detected tribe labels.

video_info

Structured metadata for attached video.

views

View or impression count.

social-db fields

34 fields

Column descriptions

Each field includes a quick meaning reference for faster query design.

bio

Author profile biography text.

bookmarks

Bookmark count.

category

Top-level topic category.

created_at

Source creation timestamp.

date

Logical partition date for analytics filtering.

engagement

Computed engagement score or rate.

followers

Follower count for the author.

friends

Following count for the author.

hashtags

Hashtag list extracted from the post.

id

Internal row identifier.

id_numeric

Numeric identifier for sorting and joins.

industry

Industry taxonomy label.

is_verified

Whether the author account is verified.

likes

Like count.

location

Author-declared location text.

major_category

Major category in hierarchical taxonomy.

media_links

Referenced media URLs.

media_type

Primary media type attached to the post.

meta_text_length

Length of post text in characters.

minor_category

Minor category in hierarchical taxonomy.

pfp_url

Profile image URL.

qt

Quote post count.

retweets

Retweet or repost count.

str_date

Date represented as raw source string.

text

Post content text.

threads

Thread-related count or marker.

tweet_id

Platform-native post identifier.

tweet_type

Post type classification label.

updated_at

Source update timestamp.

url

Source post URL.

user_name

Author username at posting time.

user_tribes

Detected tribe labels.

video_info

Structured metadata for attached video.

views

View or impression count.