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 reconcile seemingly conflicting earlier findings in the literature and 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 training a classifier
that can distinguish tweets that carry news and non-news information. We present evidence that negative sentiment does enhance virality in the news segment, but not in the non-news segment. Our findings may be summarized ’If you want to be retweeted: Sweet talk your friends or serve bad news to the public’.