We replicate and extend the analysis of the positive association between social media (Google searches and tweets) and the MTV program 16 and Pregnant recently published by Melissa Kearney and Phillip Levine (2015). We find that the relationship disappears or even turns negative when we include...

We review the economics of superstars, originally developed for stars in traditional media, and discuss whether they are applicable for the (allegedly) novel phenomenon of stars in social media (influencer, micro-celebrities). Moreover, we analyse potentially new factors for creating social...

An important part of the reform of the intelligence community is felt in the opening linked with the widening spectrum of methods and spaces which can be used to collect and analyse dates and information. One of these methods that produce large mutations in the system is connected to the world...

Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011) have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to...

The economic literature on the superstar phenomenon provides empirical evidence on different types of stars, above all athletes and musicians. A new and, to our best knowledge, unexplored area of this star theory arouse with the development of social media markets. In this paper, we analyse a...

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 present an easy to implement measure for the political position of news outlets based on politicians' selective sharing of news items. Politicians predominantly share news items that are in line with their political position, hence, one can infer the political position of news outlets from...

The importance of user-generated content is growing as media consumption is moving online; yet, investigations of media bias on user-generated content platforms are rare. We develop a novel procedure to detect coverage bias - i.e., bias in the amount of coverage certain topics or issues receive -...

There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches...

The importance of user-generated content is growing as media consumption is moving online; yet, investigations of media bias on user-generated content platforms are rare. We develop a novel procedure to detect coverage bias – i.e., bias in the amount of coverage certain topics or issues receive...