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on Cultural Economics |
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Issue of 2018‒05‒07
three papers chosen by Roberto Zanola Università degli Studi del Piemonte Orientale |
| By: | Julia Cage (Département d'économie); nicolas Hervé (Institut national de l'audiovisuel); Marie-Luce Viaud (Institut national de l'audiovisuel) |
| Abstract: | This paper documents the extent of copying and estimates the returns to originality in online news production. We build a unique dataset combining all the online content produced by French news media (newspaper, television, radio, pure online media, and a news agency) during the year 2013 with new micro audience data. We develop a topic detection algorithm that identi_es each news event, we trace the timeline of each story and study news propagation. We unravel new evidence on online news production. First, we show that one quarter of the news stories are reproduced online in less than 4 minutes. Second, we _nd that only 32.6% of the online content is original. Third, we show that reputation e_ects partly counterbalance the negative impact of plagiarism on newsgathering incentives. By using media-level daily audience and article-level social media statistics (Facebook and Twitter shares), we _nd that original content represents between 54 and 62% of online news consumption. Reputation mechanisms actually appear to solve about 30 to 40% of the copyright violation problem. |
| Keywords: | internet; information spreading; copyright; investigative journalism; social media |
| Date: | 2018–01 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/1ikqf7qv0m8h7q6lmc4ng73ueq&r=cul |
| By: | Marina Azzimonti; Marcos Fernandes |
| Abstract: | We study how the structure of social media networks and the presence of fake news might affect the degree of misinformation and polarization in a society. For that, we analyze a dynamic model of opinion exchange in which individuals have imperfect information about the true state of the world and are partially bounded rational. Key to the analysis is the presence of internet bots: agents in the network that do not follow other agents and are seeded with a constant flow of biased information. We characterize how the flow of opinions evolves over time and evaluate the determinants of long-run disagreement among individuals in the network. To that end, we create a large set of heterogeneous random graphs and simulate a long information exchange process to quantify how the bots’ ability to spread fake news and the number and degree of centrality of agents susceptible to them affect misinformation and polarization in the long-run. |
| JEL: | C45 C63 D72 D8 D83 D85 D91 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24462&r=cul |
| By: | Hopfensitz, Astrid; Mantilla, Cesar |
| Abstract: | Emotion display serves as incentives or deterrents for others’ in many social interactions. We study the portrayal of anger and happiness, two emotions associated with dominance, and its relationship to team performance in a high stake environment. We analyze 4,318 pictures of players from 304 participating teams in twelve editions (1970-2014) of the FIFA Soccer World Cup, and use automated face-reading (FaceReader 6) to evaluate the display of anger and happiness. We observe that the display of both anger and happiness is positively correlated with team performance in the World Cup. Teams whose players display more anger, an emotion associated with competitiveness, concede fewer goals. Teams whose players display more happiness, an emotion associated with confidence, score more goals. We show that this result is driven by less than half the players in a team. |
| Keywords: | emotions; facial expressions; anger; happiness; contests |
| JEL: | D91 L83 |
| Date: | 2018–04 |
| URL: | http://d.repec.org/n?u=RePEc:tse:iastwp:32633&r=cul |