Twitter User Classification with Posting Locations

Naoto Takeda; Yohei Seki

doi:10.1007/978-3-319-49304-6_35

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Twitter User Classification with Posting Locations

Naoto Takeda Yohei Seki

Year: 2016 Lecture notes in computer science Pages: 297-310 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-49304-6_35

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Keywords:

Computer science Housewife Reputation Baseline (sea) Class (philosophy) Feature (linguistics) Information retrieval World Wide Web Measure (data warehouse) Data mining Artificial intelligence

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0.00

FWCI (Field Weighted Citation Impact)

Refs

0.22

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Spam and Phishing Detection

Physical Sciences → Computer Science → Information Systems

Complex Network Analysis Techniques

Physical Sciences → Physics and Astronomy → Statistical and Nonlinear Physics

Twitter User Classification with Posting Locations

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Topics

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