entity
payload section. They are programmatically assigned based on what is explicitly mentioned (named-entity recognition) in the Post text.
entities
field and are reflected as annotations in the payload. Each annotation has a confidence score and indicates where in the Post text the entities were identified (using start
and end
fields).
The entity annotation types include:
context_annotations
field of the payload. They are inferred based on semantic analysis of keywords, hashtags, handles, etc., in the Post text and result in domain and/or entity labels. Currently, we use 80+ domains, as shown in the table below.
Domain Categories | Domain Codes |
---|---|
3: TV Shows | 46: Brand Category |
4: TV Episodes | 47: Brand |
6: Sports Events | 48: Product |
10: Person | 54: Musician |
11: Sport | 55: Music Genre |
12: Sports Team | 56: Actor |
13: Place | 58: Entertainment Personality |
22: TV Genres | 60: Athlete |
23: TV Channels | 65: Interests and Hobbies Vertical |
26: Sports League | 66: Interests and Hobbies Category |
27: American Football Game | 67: Interests and Hobbies |
28: NFL Football Game | 68: Hockey Game |
29: Events | 71: Video Game |
31: Community | 78: Video Game Publisher |
35: Politicians | 79: Video Game Hardware |
38: Political Race | 83: Cricket Match |
39: Basketball Game | 84: Book |
40: Sports Series | 85: Book Genre |
43: Soccer Match | 86: Movie |
44: Baseball Game | 87: Movie Genre |
45: Brand Vertical | 88: Political Body |
46: Brand Category | 89: Music Album |
47: Brand | 90: Radio Station |
48: Product | 91: Podcast |
54: Musician | 92: Sports Personality |
55: Music Genre | 93: Coach |
56: Actor | 94: Journalist |
58: Entertainment Personality | 95: TV Channel [Entity Service] |
60: Athlete | 109: Reoccurring Trends |
65: Interests and Hobbies Vertical | 110: Viral Accounts |
66: Interests and Hobbies Category | 114: Concert |
67: Interests and Hobbies | 115: Video Game Conference |
68: Hockey Game | 116: Video Game Tournament |
71: Video Game | 117: Movie Festival |
78: Video Game Publisher | 118: Award Show |
79: Video Game Hardware | 119: Holiday |
83: Cricket Match | 120: Digital Creator |
84: Book | 122: Fictional Character |
85: Book Genre | 130: Multimedia Franchise |
86: Movie | 131: Unified Twitter Taxonomy |
87: Movie Genre | 136: Video Game Personality |
88: Political Body | 137: eSports Team |
89: Music Album | 138: eSports Player |
90: Radio Station | 139: Fan Community |
91: Podcast | 149: Esports League |
92: Sports Personality | 152: Food |
93: Coach | 155: Weather |
94: Journalist | 156: Cities |
95: TV Channel [Entity Service] | 157: Colleges & Universities |
109: Reoccurring Trends | 158: Points of Interest |
110: Viral Accounts | 159: States |
114: Concert | 160: Countries |
115: Video Game Conference | 162: Exercise & Fitness |
116: Video Game Tournament | 163: Travel |
117: Movie Festival | 164: Fields of Study |
118: Award Show | 165: Technology |
119: Holiday | 166: Stocks |
120: Digital Creator | 167: Animals |
122: Fictional Character | 171: Local News |
130: Multimedia Franchise | 172: Global TV Show |
131: Unified Twitter Taxonomy | 173: Google Product Taxonomy |
136: Video Game Personality | 174: Digital Assets & Crypto |
137: eSports Team | 175: Emergency Events |
138: eSports Player |
How does Twitter context annotations work?
How do I know that your data is complete and trustworthy?
How do you ensure precision?
How do you decide what to track?
What historical support is available with Tweet Annotations?
Is Twitter able to annotate Tweets in non-english languages? If so, which languages and does the coverage of Tweets being annotated change?
Rank | Country code | Country | % of Tweets annotated |
---|---|---|---|
1 | IN | India | 41% |
2 | VN | Vietnam | 36% |
3 | GB | Great Britain | 36% |
4 | EC | Ecuador | 35% |
5 | PE | Peru | 33% |
6 | US | United States | 32% |
7 | CA | Canada | 32% |
8 | AU | Australia | 31% |
9 | JP | Japan | 31% |
10 | PH | Philippines | 30% |
11 | SG | Singapore | 30% |
12 | MY | Malaysia | 30% |
13 | MX | Mexico | 30% |
14 | GB | Great Britain | 29% |
15 | NG | Nigeria | 29% |
What underlying 'semantics' does Twitter rely on to annotate a Tweet?
Why do some Tweets have entities associated with them while others do not?
When there are multiple domains (for example, [3,30]), does the Entity ID remain the same?
Do you have an established timeline for show/movie tracking? In other words, how long is a show/movie tracked before/after release?
Do movies have a locale filter similar to the one for TV shows?