Identifying Automatic Posting Systems in Microblogs

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

laboreiro, g (Author) Other; sarmento, l (Author) Other; oliveira, e (Author) FEUP

Conference proceedings International

Title: PROGRESS IN ARTIFICIAL INTELLIGENCE

Pages: 634-648

15th Portuguese Conference on Artificial Intelligence (EPIA 2011)

Lisbon, PORTUGAL, OCT 10-13, 2011

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 2 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-002-VZ1

DOI: 10.1007/978-3-642-24769-9_46

Abstract (EN): In this paper we study the problem of identifying systems that automatically inject non-personal messages in micro-blogging message streams; thus potentially biasing results of certain information extraction procedures, such as opinion-mining and trend analysis. We also study several classes of features, namely features based on the time of posting, the client used to post, the presence of links, the user interaction and the writing style. This last class of features, that we introduce here for the first time; is proved to be a top performer, achieving accuracy near the 90%, on par with the best features previously used for this task.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15