Visual Sentiment Analysis of RSS News Feeds Featuring the US Presidential Election in 2008

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Visual Interfaces to the Social and the Semantic Web (VISSW 2009), Sanibel Island, Florida, 8th February 2009. 2009
Zusammenfassung

The technology behind RSS feeds offers great possibilities to retrieve more news items than ever. In contrast to these technical developments, human capabilities to read all these news items have not increased likewise. To bridge this gap, this paper presents a visual analytics tool for conducting semi-automatic sentiment analysis of large news feeds. While the tool automatically retrieves and analyzes RSS feeds with respect to positive and negative opinion words, the more demanding news analysis of finding trends, spotting peculiarities and putting events into context is left to the human expert. For a solid analysis the news similarity filter enables highlighting of similar or redundant news items. A case study about news related to the US presidential election in 2008 shows how the visual interface of the tool empowers the analyst to draw meaningful conclusions without the effort of reading all news postings.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
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Opinion mining, sentiment analysis, information visualization, visual analytics
Konferenz
VISSW, 8. Feb. 2009, Sanibel Island, Florida
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Zitieren
ISO 690WANNER, Franz, Christian ROHRDANTZ, Florian MANSMANN, Daniela OELKE, Daniel A. KEIM, 2009. Visual Sentiment Analysis of RSS News Feeds Featuring the US Presidential Election in 2008. VISSW. Sanibel Island, Florida, 8. Feb. 2009. In: Visual Interfaces to the Social and the Semantic Web (VISSW 2009), Sanibel Island, Florida, 8th February 2009. 2009
BibTex
@inproceedings{Wanner2009Visua-5946,
  year={2009},
  title={Visual Sentiment Analysis of RSS News Feeds Featuring the US Presidential Election in 2008},
  booktitle={Visual Interfaces to the Social and the Semantic Web (VISSW 2009), Sanibel Island, Florida, 8th February 2009},
  author={Wanner, Franz and Rohrdantz, Christian and Mansmann, Florian and Oelke, Daniela and Keim, Daniel A.}
}
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    <dcterms:abstract xml:lang="eng">The technology behind RSS feeds offers great possibilities to retrieve more news items than ever. In contrast to these technical developments, human capabilities to read all these news items have not increased likewise. To bridge this gap, this paper presents a visual analytics tool for conducting semi-automatic sentiment analysis of large news feeds. While the tool automatically retrieves and analyzes RSS feeds with respect to positive and negative opinion words, the more demanding news analysis of finding trends, spotting peculiarities and putting events into context is left to the human expert. For a solid analysis the news similarity filter enables highlighting of similar or redundant news items. A case study about news related to the US presidential election in 2008 shows how the visual interface of the tool empowers the analyst to draw meaningful conclusions without the effort of reading all news postings.</dcterms:abstract>
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