We study social reactions to job destructions on Twitter. We use information on large-scale restructuring events announced in the United Kingdom over the period 2013-2018. We match it with data collected on Twitter regarding the number and sentiments of the tweets posted around the time of the...

We study the reactions to job destructions on Twitter. We use information on large-scale job-destruction and job-creation events announced in the United Kingdom over the period 2013-2018. We match it with data collected on Twitter regarding the number and sentiments of the tweets posted around...

We study the reactions to job destructions on Twitter. We use information on large-scale job-destruction and job-creation events announced in the United Kingdom over the period 2013-2018. We match it with data collected on Twitter regarding the number and sentiments of the tweets posted around...

A main characteristic of social media is that its diverse content, copiously generated by both standard outlets and general users, constantly competes for the scarce attention of large audiences. Out of this flood of information some topics manage to get enough attention to become the most...

We present a method for accurately predicting the long time popularity of online content from early measurements of user's access. Using two content sharing portals, Youtube and Digg, we show that by modeling the accrual of views and votes on content offered by these services we can predict the...

In recent years, social media has become ubiquitous and important for social networking and content sharing. And yet, the content that is generated from these websites remains largely untapped. In this paper we demonstrate how social media content can be used to predict real-world outcomes. In...

Scholars, advertisers and political activists see massive online social networks as a representation of social interactions that can be used to study the propagation of ideas, social bond dynamics and viral marketing, among others. But the linked structures of social networks do not reveal...

We present an analysis of user conversations in on-line social media and their evolution over time. We propose a dynamic model that accurately predicts the growth dynamics and structural properties of conversation threads. The model successfully reconciles the differing observations that have...

The ever-increasing amount of information owing through Social Media forces the members of these networks to compete for attention and influence by relying on other peopleto spread their message. A large study of information propagation within Twitter reveals that the majority of users act as...