Abstract

Tweets contain mentions of numerous entities, persons and events, and often additional information, like an opinion, that can be viewed as an annotation of that entity. However, this information is currently being accumulated only by specific applications without being made available in a generic format. We discuss a natural language processing approach to extract information about entities and their annotations from tweets and transform them into a semantic, reusable knowledge base. We believe this will greatly facilitate access to user-generated Twitter data for many applications.

Keywords:
Computer science Information retrieval Annotation Semantic annotation Knowledge base Semantics (computer science) Entity linking World Wide Web Natural language Named entity Natural language processing Artificial intelligence

Metrics

23
Cited By
3.13
FWCI (Field Weighted Citation Impact)
6
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
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