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The Role of Emotional Variables in the Classification and Prediction of Collective Social Dynamics

100%
Chołoniewski J., Sienkiewicz J., Hołyst J., Thelwall M.
Acta Physica Polonica A
|
2015
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vol. 127
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issue 3A
A-21-A-28
EN
We demonstrate the power of data mining techniques for the analysis of collective social dynamics within British Tweets during the Olympic Games 2012. The classification accuracy of online activities related to the successes of British athletes significantly improved when emotional components of tweets were taken into account, but employing emotional variables for activity prediction decreased the classifiers' quality. The approach could be easily adopted for any prediction or classification study with a set of problem-specific variables.
2
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Statistical Analysis of Emotions and Opinions at Digg Website

88%
Pohorecki P., Sienkiewicz J., Mitrović M., Paltoglou G., Hołyst J.
Acta Physica Polonica A
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2013
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vol. 123
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issue 3
604-615
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.
3
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Emotional Analysis of Blogs and Forums Data

76%
Weroński P., Sienkiewicz J., Paltoglou G., Buckley K., Thelwall M., Hołyst J.
Acta Physica Polonica A
|
2012
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vol. 121
|
issue 2B
B-128-B-132
EN
We perform a statistical analysis of emotionally annotated comments in two large online datasets, examining chains of consecutive posts in the discussions. Using comparisons with randomised data we show that there is a high level of correlation for the emotional content of messages.
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