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2013 | 123 | 3 | 604-615
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Statistical Analysis of Emotions and Opinions at Digg Website

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Abstracts
EN
We performed statistical analysis on data from the Digg.com website, which enables its users to express their opinion on news stories by taking part in forum-like discussions as well as to directly evaluate previous posts and stories by assigning so called "diggs". Owing to fact that the content of each post has been annotated with its emotional value, apart from the strictly structural properties, the study also includes an analysis of the average emotional response of the comments about the main story. While analysing correlations at the story level, an interesting relationship between the number of diggs and the number of comments that a story received was found. The correlation between the two quantities is high for data where small threads dominate and consistently decreases for longer threads. However, while the correlation of the number of diggs and the average emotional response tends to grow for longer threads, correlations between numbers of comments and the average emotional response are almost zero. We also suggest presence of two different mechanisms governing the evolution of the discussion and, consequently, its length.
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author
  • Faculty of Physics, Center of Excellence for Complex Systems Research, Warsaw University of Technology, Koszykowa 75, PL-00-662 Warsaw, Poland
  • Faculty of Physics, Center of Excellence for Complex Systems Research, Warsaw University of Technology, Koszykowa 75, PL-00-662 Warsaw, Poland
author
  • Department of Theoretical Physics, Jožef Stefan Institute, P.O. Box 3000, 1001 Ljubljana, Slovenia
author
  • Statistical Cybermetrics Research Group, School of Technology, University of Wolverhampton, Wulfruna Str., WV1 1LY Wolverhampton, United Kingdom
author
  • Faculty of Physics, Center of Excellence for Complex Systems Research, Warsaw University of Technology, Koszykowa 75, PL-00-662 Warsaw, Poland
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv123n319kz
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