Visual sentiment analysis on Twitter data streams

Hao, Ming; Rohrdantz, Christian; Janetzko, Halldor; Dayal, Umeshwar; Keim, Daniel A.; Haug, Lars-Erik; Hsu, Mei-Chun

Visual sentiment analysis on Twitter data streams

Dateien

Hao_190485.pdfGröße: 1.12 MBDownloads: 2812

Datum

2011

Autor:innen

Hao, Ming

Rohrdantz, Christian

Janetzko, Halldor

Dayal, Umeshwar

Keim, Daniel A.

Haug, Lars-Erik

Hsu, Mei-Chun

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

2011 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2011, pp. 277-278. ISBN 978-1-4673-0015-5. Available under: doi: 10.1109/VAST.2011.6102472

Zusammenfassung

Twitter currently receives about 190 million tweets (small textbased Web posts) a day, in which people share their comments regarding a wide range of topics. A large number of tweets include opinions about products and services. However, with Twitter being a relatively new phenomenon, these tweets are underutilized as a source for evaluating customer sentiment. To explore high-volume twitter data, we introduce three novel timebased visual sentiment analysis techniques: (1) topic-based sentiment analysis that extracts, maps, and measures customer opinions; (2) stream analysis that identifies interesting tweets based on their density, negativity, and influence characteristics; and (3) pixel cell-based sentiment calendars and high density geo maps that visualize large volumes of data in a single view. We applied these techniques to a variety of twitter data, (e.g., movies, amusement parks, and hotels) to show their distribution and patterns, and to identify influential opinions.

Fachgebiet (DDC)

004 Informatik

Konferenz

2011 IEEE Conference on Visual Analytics Science and Technology (VAST), 23. Okt. 2011 - 28. Okt. 2011, Providence, RI, USA

Zitieren

ISO 690

HAO, Ming, Christian ROHRDANTZ, Halldor JANETZKO, Umeshwar DAYAL, Daniel A. KEIM, Lars-Erik HAUG, Mei-Chun HSU, 2011. Visual sentiment analysis on Twitter data streams. 2011 IEEE Conference on Visual Analytics Science and Technology (VAST). Providence, RI, USA, 23. Okt. 2011 - 28. Okt. 2011. In: 2011 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2011, pp. 277-278. ISBN 978-1-4673-0015-5. Available under: doi: 10.1109/VAST.2011.6102472

BibTex

@inproceedings{Hao2011-10Visua-19048,
  year={2011},
  doi={10.1109/VAST.2011.6102472},
  title={Visual sentiment analysis on Twitter data streams},
  isbn={978-1-4673-0015-5},
  publisher={IEEE},
  booktitle={2011 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  pages={277--278},
  author={Hao, Ming and Rohrdantz, Christian and Janetzko, Halldor and Dayal, Umeshwar and Keim, Daniel A. and Haug, Lars-Erik and Hsu, Mei-Chun}
}

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Universitätsbibliographie

Ja