The link between affect, defined as the capacity for sentimental arousal on the part of a message, and virality, defined as the probability that it be sent along, is of significant theoretical and practical importance, e.g. for viral marketing. The basic measure of virality in Twitter is the probability of retweet and we are interested in which dimensions of the content of a tweet leads to retweeting. We hypothesize that negative news content is more likely to be retweeted, while for non-news tweets positive sentiments support virality. To test the hypothesis we analyze three corpora: A complete sample of tweets about the COP15 climate summit, a random sample of tweets, and a general text corpus including news. The latter allows us to train a classifier that can distinguish tweets that carry news and non-news information. We present evidence that negative sentiment enhances virality in the news segment, but not in the non-news segment. Our findings may be summarized 'If you want to be cited: Sweet talk your friends or serve bad news to the public'. © 2011 Springer-Verlag.

Hansen, L., Arvidsson, A., Nielsen, F., Colleoni, E., Etter, M. (2011). Good friends, bad news - Affect and virality in twitter. In 6th International Conference on Future Information Technology, FutureTech 2011; Loutraki; Greece; 28-30 June 2011 (pp. 34-43). Springer Verlag [10.1007/978-3-642-22309-9_5].

Good friends, bad news - Affect and virality in twitter

COLLEONI, ELANOR
Penultimo
;
2011

Abstract

The link between affect, defined as the capacity for sentimental arousal on the part of a message, and virality, defined as the probability that it be sent along, is of significant theoretical and practical importance, e.g. for viral marketing. The basic measure of virality in Twitter is the probability of retweet and we are interested in which dimensions of the content of a tweet leads to retweeting. We hypothesize that negative news content is more likely to be retweeted, while for non-news tweets positive sentiments support virality. To test the hypothesis we analyze three corpora: A complete sample of tweets about the COP15 climate summit, a random sample of tweets, and a general text corpus including news. The latter allows us to train a classifier that can distinguish tweets that carry news and non-news information. We present evidence that negative sentiment enhances virality in the news segment, but not in the non-news segment. Our findings may be summarized 'If you want to be cited: Sweet talk your friends or serve bad news to the public'. © 2011 Springer-Verlag.
Capitolo o saggio
Social media; Communication; Data mining; Corporate communication; Computer Science (all)
English
6th International Conference on Future Information Technology, FutureTech 2011; Loutraki; Greece; 28-30 June 2011
2011
978-364222308-2
185, issue part II
Springer Verlag
34
43
Hansen, L., Arvidsson, A., Nielsen, F., Colleoni, E., Etter, M. (2011). Good friends, bad news - Affect and virality in twitter. In 6th International Conference on Future Information Technology, FutureTech 2011; Loutraki; Greece; 28-30 June 2011 (pp. 34-43). Springer Verlag [10.1007/978-3-642-22309-9_5].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/66062
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